Anthropic, PBC files S-1 for IPO

Cover page 24 changes

CONFIDENTIAL TREATMENT REQUESTED BY ANTHROPIC, PBC

PURSUANT TO 17 C.F.R. SECTION 200.83

This amended draft registration statement has not been publicly filed with the

Securities and Exchange Commission and all information herein remains strictly confidential.

anthropicpbc-sx1.htm

As confidentially submitted to filed with the Securities and Exchange Commission on October 9, 26, 2026.

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CONFIDENTIAL TREATMENT REQUESTED BY ANTHROPIC, PBC

PURSUANT TO 17 C.F.R. SECTION 200.83

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Select Market under the symbol ANT.

Immediately prior to the completion of this offering, we will also issue a single share of Class F common stock, a special class of our common stock, to a limited liability company organized by our co-founders (the Founder LLC ). Dario Amodei, our Chief Executive

Prior to this offering, there has been no public market for our Class A common stock. It is currently estimated that the initial public offering price per share will be between $ and $ . We have applied to list our Class A common stock on the Nasdaq Global Select Market under the symbol ANT.

We have a novel capital and corporate governance structure. We are incorporated as a public benefit corporation under Delaware law, a structure consistent with our commitment to artificial intelligence ( AI ) safety and responsibility. As a public benefit corporation, we are required to balance the pecuniary interests of our stockholders, the best interests of those materially affected by our conduct, and the specific public benefit purpose identified in our amended and restated certificate of incorporation the responsible development and maintenance of advanced AI for the long-term benefit of humanity. We created our Long-Term Benefit Trust (the LTBT ) to help ensure that Anthropic, PBC is managed in a manner that responsibly balances its goals as a public benefit corporation. The LTBT is intended to operate as an independent body of financially disinterested trustees with expertise in AI safety, national security, public policy, and social enterprise. Through a special class of common stock, Class T common stock, the LTBT generally has the authority to elect and remove the

Class T common stock, the LTBT generally has the authority to elect and remove the Class T directors, who together will constitute a majority of the authorized members of our board of directors. The Our Class T common stock does not otherwise have voting rights with respect to matters submitted to stockholders generally and has no economic rights. Immediately prior to the completion of this offering, we will also issue a single share of Class F common stock, a special class of our common stock, to a limited liability company organized by our co-founders (the Founder

LLC ). Dario Amodei, our Chief Executive Officer and a member of our board of directors, and Daniela Amodei, our President and Chairperson of our board of directors, together with our five other co-founders, will initially be the sole members of the Founder LLC. The Our Class F common stock, which will be held by the Founder LLC, will be entitled to an aggregate number of votes that equals 50.1% of the total voting power of our outstanding shares of capital stock with respect to matters submitted to stockholders generally, including the election of our directors other than the Class T directors. The Our Class F common stock will not have any economic rights. Upon the completion of this offering, we will also authorize a special class of our common stock, Class E common stock, which will be issued to our employees, excluding our co-founders. The Our Class E common stock will be entitled to vote only on certain limited matters and will not have any economic rights. In addition, we have authorized Class A common stock and Class N common stock. The rights of the holders of Class A common stock and Class N common stock are identical, except with respect to voting and conversion. Each share of Class A common stock is entitled to one vote per share and shares of Class N common stock have no voting rights, except as otherwise required by law. The holders of our Class N common stock are primarily strategic business partners, and shares of Class N common stock will generally convert to Class A common stock upon a sale or transfer to an unaffiliated third party. The Class A common stock is not convertible. See the sections titled Risk Factors Risks Related to our Governance Structure, Our Governance Structure and Its Goals, and Description of Capital Stock for more information.

Class A common stock and Class N common stock. The rights of the holders of Class A common stock and Class N common stock are identical, except with respect to voting and conversion. Each share of Class A common stock is entitled to one vote per share and shares of Class N common stock have no voting rights, except as otherwise required by law. The holders of our Class N common stock are primarily strategic business partners, and shares of Class N common stock will generally convert to Class A common stock upon a sale or transfer to an unaffiliated third party. Our Class A common stock is not convertible. See the sections titled Risk Factors Risks Related to our Governance Structure, Our

See the sections titled Our Governance Structure and Its Goals, Management, and Description of Capital Stock for additional more information.

We are considered a controlled company within the meaning of the Nasdaq Global Select Market corporate governance requirements. See the sections titled Our Governance Structure and Its Goals, Management, and Description of Capital Stock for additional information.

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CONFIDENTIAL TREATMENT REQUESTED BY ANTHROPIC, PBC

PURSUANT TO 17 C.F.R. SECTION 200.83

Wells Fargo Securities

Deutsche Bank Securities

Capital One Securities

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CONFIDENTIAL TREATMENT REQUESTED BY ANTHROPIC, PBC

PURSUANT TO 17 C.F.R. SECTION 200.83

Select defined terms 1 change

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Constitutional AI refers to our an approach to training AI models using a set of written principles, which we refer to as Claude s constitution, currently organized around four priorities being broadly safe, broadly ethical, compliant with our guidelines, and genuinely helpful. Under Constitutional AI, our models evaluate, critique, and revise their own responses against these principles, enabling us to define and control model behavior through auditable principles, rather than relying solely on fixed rule-based instructions or human reviewers.

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Prospectus summary 83 changes

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Anthropic was founded in 2021 by a team of researchers responsible for man y of the breakthroughs that define AI. We are first and foremost a research lab our mission is the responsible development and maintenance of advanced AI for the long-term benefit of humanity. This mission directs our focus and, together along with our talent and culture, our frontier and safety research, our approach to compute, and our enterprise strategy, forms it is one of the core advantages that set us apart. These advantages enable us to continuously advance frontier AI and shape the standards for its safe and responsible development. Our frontier AI, Claude, is delivered to customers through our models, platform, and applications. Claude has experienced the fastest enterprise adoption of any technology in history, as demonstrated by revenue growing from $0 at commercial launch in the first quarter of 2023 to $ for the three months ended . September 30, 2026. This rapid and growing adoption generates two self- reinforcing self-reinforcing dynamics an improvement loop that advances Claude and an investment loop that helps fund our continued research in frontier AI.

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Frontier & Safety Research. We believe that sustained, focused research at the frontier of intelligence is required to build the most capable and safest AI systems. Our frontier AI capabilities and safety research are deeply integrated and directly shape model design, training, and deployment, helping us produce systems that are more reliable, steerable, and well-suited for real-world deployment, particularly in demanding enterprise environments. We translate our research leadership into innovation velocity, and have consistently released better models, platform capabilities, and applications. Each version of a Claude model is used to build assists in building the next, helping to compress development timelines and produce compounding improvements in the speed at which we innovate. We refer to this recursive dynamic as closing the loop, and we believe it is one of the most significant structural advantages in frontier AI.

Our Approach to Compute . We procure manage compute as a single, fungible pool from multiple strategic partners, and we dynamically direct available compute between workloads based on where the marginal unit is expected to be most productive at any given time. We believe that this approach to compute enables us to deliver superior models, serve more customers, and achieve greater productivity from our compute investment. This compute efficiency creates the foundation for us to advance the frontier of AI capabilities through research and model development, meet growing demand from customers, and provide for internal usage of Claude. We have achieved this through our research breakthroughs and our multi-chip compute architecture across AWS Trainium, Google TPUs, NVIDIA GPUs, and AMD GPUs, enabling us to orchestrate workloads to optimize for price and performance . To support our research, model development, customer demand, and internal usage of Claude, we continue to invest at scale. As of , and subsequent to September 30, 2026, we have entered into purchase commitments and lease agreements, including short-term commitments, as well as leases not yet commenced, with an aggregate committed spend of more than $ , substantially all of which is related to compute and infrastructure. and we expect These commitments will continue include approximately $ expected to increase. See the section titled Management s Discussion and Analysis of Financial Condition be incurred before December 31, 2030, and Results substantially all of Operations Liquidity the remainder is expected to be incurred between 2031 and Capital Resources Contractual Obligations for more information. 2045.

Approximately $ of these commitments are due in the next 12 months. See the section titled Management s Discussion and Analysis of Financial Condition and Results of Operations Liquidity and Capital Resources Contractual Obligations for more information.

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Our A Near-Term Opportunity is to Transform Cognitive Work

Frontier AI is transforming cognitive work the application of knowledge, reasoning, and judgment to produce economic value. We believe it will make humans far more capable and expand the world s overall capacity for that work, including accelerating scientific discovery and helping businesses grow. Knowledge workers are the leading edge of this opportunity. As frontier AI advances, more capable models can unlock entirely new use cases while also efficiently serving a wide range of cognitive work at scale across the capability-cost-speed curve. We believe the work that knowledge workers perform represented more than $40 trillion in economic 1 See the section titled Industry, Market, and Other Data for a description of how we calculate annual economic value attributable to knowledge workers globally.

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4 IDC, Worldwide Developer Population Growth Forecast, 2025 2029, doc # US53789825, September 2025.

cases while also efficiently serving a wide range of cognitive work at scale across the capability-cost-speed curve. We believe the work that knowledge workers perform represented more than $40 trillion in economic value globally in 2025, 1 and with frontier AI s potential to make them meaningfully more productive, our near- term opportunity is to expand this value and accelerate economic growth. While it is still early to forecast frontier AI s full impact across the economy, International Data Corporation ( IDC ) estimates that investment in AI solutions and services will yield a cumulative global economic impact of $22.5 trillion by 2031. 2 We believe the impact could be even greater.

Frontier AI May Reshape Entire Sectors and Accelerate Novel Discoveries We believe frontier AI represents a larger opportunity than any prior technology cycle, and Claude is already demonstrating this potential. Claude can now execute complex projects autonomously and turn open-ended tasks into finished, high-quality deliverables. These capabilities enable it to transform the largest sectors of the economy, driving meaningful gains in productivity and output. Frontier AI s capabilities may extend beyond current markets to open entirely new ones, reaching domains such as robotics, advanced manufacturing, and logistics, and accelerating progress in scientific research, including drug discovery and materials science. For example, in the life sciences sector, where annual global pharmaceutical spend is expected to exceed $2 trillion in 2026, 3 Claude is used in drug discovery and development by our customers, our biotechnology partners, and our own researchers. We are also extending Claude into robotics, where our Model Hardware Standard ( MHS ) enables AI agents to operate lab and manufacturing equipment such as microscopes, liquid handlers, and off-the-shelf robotic arms. Ultimately, we believe frontier AI will help drive global economic growth. As frontier AI makes workers and organizations more productive, becomes embedded in the products and services they deliver, and unlocks new business models, it creates economic output that did not previously exist. We believe our opportunity is to capture a share not only of today s economic activity but also of that newly created output as the global economy expands.

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We believe that frontier AI companies must invest in safety to help ensure the responsible diffusion of this technology . We also believe that safety and ethical behavior resonate particularly strongly with enterprises, where rigorous safeguards, predictable model behavior, and demonstrable accountability have become decisive criteria in selecting an AI partner for mission-critical workloads.

While the potential benefits of AI are extraordinary, its rapid advancement will impact the economy and society in ways that could create significant dislocation, disruption, particularly if the technology is not developed and deployed responsibly. For example, bad actors have already conducted high-profile cyberattacks using AI s capabilities to discover vulnerabilities, generate malware, and evade detection tools other risks associated with misuse, including in the domain of biology, could result in even greater harm. AI deployed at scale also has the potential to concentrate power and wealth both within and between countries in ways that could erode trust, harm society, and destabilize the geopolitical order. In addition, Misaligned AI systems could corrupt institutional decision-making, decision- making or cause large-scale harm through opaque autonomous actions that are not visible or unsteerable behavior, understandable to their users and erode operators. We believe that frontier AI companies must invest in safety and alignment to help ensure the trust responsible diffusion of this technology. We also believe that makes complex economic safety, alignment, and social systems function. ethical behavior resonate particularly strongly with enterprises, where rigorous safeguards, predictable model behavior, and demonstrable accountability have become decisive criteria in selecting an AI partner for mission-critical workloads.

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We believe we have reached an inflection point where AI systems can function as genuine collaborators in professional work. They quickly complete substantive tasks that might otherwise occupy a skilled professional for several hours, a full day, or longer. AI systems are also becoming increasingly capable of performing tasks that were previously too difficult or costly to complete or surfacing original insights and analyses. We refer to these AI systems that work alongside humans to perform complex, multi-step work at professional levels as Virtual Collaborators. Virtual Collaborators carry the access rights, system connections, and context needed that their organizations grant them, which allows them to function more accurately and reliably. They can navigate and use internal tools and execute workflows that span multiple steps that require sustained reasoning. Virtual Collaborators are AI designed to be embedded where work gets done, and our aim is to continue extending them to knowledge workers globally, a population that is estimated to exceed one billion in 2028. 4 Claude Code. The clearest manifestation of Virtual Collaborators today is Claude Code, our coding agent and the product we believe has most concretely defined what autonomous AI work looks like. Claude Code shifted the market s understanding of what an AI system could do alongside a software IDC, Worldwide Developer it not only suggests the next line of code, but also plans, writes, tests, and debugs all the way to production-grade code that is ready to ship. Within months of its release, autonomous coding became the reference point for measuring the progress of frontier AI. For enterprise AI use cases, we believe the launch of Claude Code was comparable in its impact to the introduction of the first widely adopted conversational AI assistants. What makes Claude Code a Virtual Collaborator is its sustained reasoning, a harness that translates intent into actions, a sandboxed virtual environment that maintains a persistent state, integration with existing tools and systems, and a user-friendly interface. Its uses are highly varied and often surprising for example, NASA engineers used Claude Code to plan, write, and execute navigation commands for the Mars Perseverance rover, resulting in the first AI- planned drive on Mars. Population Growth Forecast, 2025 2029, doc # US53789825, September 2025.

Collaborators are AI designed to be embedded where work gets done, and our aim is to continue extending them to knowledge workers globally, a population that is estimated to exceed one billion in 2028. 4 Claude Code. The clearest manifestation of Virtual Collaborators today is Claude Code, our coding agent and the product we believe has most concretely defined what autonomous AI work looks like. Claude Code shifted the market s understanding of what an AI system could do in collaboration with software developers the model suggests the next line of code and goes further by planning, writing, testing, and debugging a process that results in production-grade code. Within months of its release, autonomous coding became the reference point for measuring the progress of frontier AI. For enterprise AI use cases, we believe the launch of Claude Code was comparable in its impact to the introduction of the first widely adopted conversational AI assistants. What makes Claude Code a Virtual Collaborator is its sustained reasoning, a harness that translates intent into actions, an execution environment that maintains a persistent state whether on a developer s machine or in a sandboxed cloud environment, integration with existing tools and systems, and a user-friendly interface. Its uses are highly varied and often surprising for example, NASA engineers used Claude Code to plan and write navigation commands for the Mars Perseverance rover, resulting in the first AI-planned drive on Mars.

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Claude Cowork. All digital work is ultimately an expression of code, and Claude s mastery of it powers Virtual Collaborators capable of handling complex work far beyond software development. Claude Cowork extends the same agentic architecture of Claude Code to knowledge workers broadly by translating a user s intent into completed work, autonomously reading files, navigating applications, and executing multi-step workflows on a user s desktop while the underlying code is abstracted away. By extending beyond Claude Code with applications purpose-built for specific professions and industry verticals, we accelerate Claude s diffusion into new categories of knowledge work and deepen our presence across the enterprise. As of , September 30, 2026, adoption of Claude Cowork, which we made available as a research preview in January 2026, outpaced the adoption Claude Code achieved at the equivalent point following its research preview release in February 2025.

In September 2026, we began merging Claude Cowork and Claude.ai, bringing agentic and conversational work into a unified application. Users can now move from a simple question to complex, multi-step tasks in the same conversation.

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The speed and depth of our enterprise customer adoption are powerful evidence of Claude s position at the frontier of AI. Our customer base as of September 30, 2026 includes More than 11,900 customers with $100,000 or more of revenue on a TTM basis More than 1,900 customers with $1 million or more of revenue on a TTM basis and Approximately 250 customers with $10 million or more of revenue on a TTM basis.

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Our commitment to our mission instills confidence in our customers to choose Claude as a trusted partner. Our investments in alignment research on AI alignment, interpretability, cybersecurity, and enterprise-grade controls aim to deliver the predictability and dependability that organizations need in customer-facing and regulated contexts. This trust expands the scope of work that enterprises delegate to Claude and the systems into which they integrate Claude. Enterprises are aligning their strategies around Claude with confidence that we are building frontier AI to serve their needs for the long term.

This trust means that enterprises can expand the scope of the work that they delegate to Claude, as well as the systems into which Claude is integrated. Enterprises are aligning their strategies around Claude with the confidence that we are building frontier AI that serves their needs in the long term.

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Diffusion also accelerates as our models become more capable and efficient, allowing us to lower the cost per task for customers. For example, Claude Opus 5.5 reduced customer costs per task by approximately 40% compared to Claude Opus 5. Lower costs drive greater usage, which in turn drives broader diffusion of Claude. Our compute efficiency allows us to deliver these reductions while preserving our margins.

Building and scaling frontier AI is one of the most important and capital-intensive endeavors in history. Our financial model provides us with the following strengths that allow us to build and scale efficiently Rapid Revenue Growth. Our enterprise strategy is designed to drive durable customer adoption by embedding Claude directly into business-critical workflows and enabling the development of products built on Claude. We believe that enterprise customers achieve a compelling return on investment from Claude, as agentic workflows can drive both top-line growth and efficiency. This enables us to expand quickly with customers, as demonstrated by our Net Revenue Retention of approximately 900 % as of . September 30, 2026. Diffusion also accelerates as our models become more capable and efficient, allowing us to lower the cost per task for customers. For example, Claude Opus 5.5 reduced customer costs per task by approximately 40% compared to Claude Opus 5. Lower costs per task drive greater usage, which in turn drives broader diffusion of Claude. Our compute efficiency allows us to deliver these reductions while preserving our margins.

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Operating Efficiency . Our operating efficiency, derived from our high talent density, our efficient go- to-market, and how extensively our teams leverage Claude in their work, enables us to scale with a smaller team relative to other large enterprise technology companies. Our operating efficiency is demonstrated by TTM revenue per employee of $ over $6.6 million as of , September 30, 2026, compared to $ $1.4 million as of . September 30, 2025.

The demonstrated growth, scale, and efficiency of our financial model help us to continue making significant long-term investments to build frontier AI responsibly. Our business trajectory and financial profile have enabled us to access capital and secure compute from investors and partners. As of June 30, 2026, we have had raised an aggregate of $141.1 billion of capital and have had cash and cash equivalents of $112.4 billion and short- term investments of $19.3 billion .

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As part of these initiatives, we will contribute contributed 846,840,960 shares of our Class N common stock, prior to the completion of this offering, representing 5 % of our fully-diluted fully diluted shares outstanding as of June 30, 2026 (assuming full conversion of the Amazon Notes, as defined below) , to Anthropic Public Benefit Fund, LLC (the Anthropic Public Benefit Entity Fund ), our wholly owned subsidiary dedicated to the Company Purpose (as defined below) subject to stockholder approval (such issuance, the Initial Public Benefit Issuance ). Our board of directors has also approved a framework under which it may, in its discretion, contribute issue shares of our Class N common stock to the Anthropic Public Benefit Fund (or other designee) representing up to an additional % 2% of our then-outstanding equity shares (plus any shares subject to options, restricted stock units, and other convertible securities and any shares held by the Anthropic Public Benefit Entity (or other designee) Fund) each time our share price appreciates 50 % above the price at which the prior contribution was made, share price milestone , beginning with our initial public offering price (the Public Benefit Issuances ). In addition, our co-founders have each pledged to dedicate 80% of their personal equity in Anthropic to philanthropic causes. For additional information regarding these pledges, including related risks, see the section titled Risk Factors Risks Related to Ownership of our Class A Common Stock. Separate from the co-founders pledges, we also maintain a donation matching program through which employees can pledge a meaningful portion of their equity awards toward charitable giving, which we match with shares of our Class N Common Stock.

Separate from the co-founders pledges, we also maintain a donation matching program through which employees can pledge a meaningful portion of their equity awards toward charitable giving, which we match with shares of our Class N common stock.

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In 2023, we implemented an innovative governance structure featuring the LTBT, which is designed to ensure that we are managed in a manner that responsibly balances our tripartite goals as a PBC the pecuniary interests of our stockholders, the best interests of those materially affected by our conduct, and the Company Purpose. The LTBT is intended to operate as an independent body of five financially disinterested voting trustees ( Trustees ) with expertise in AI safety, national security, public policy, and social enterprise. Through a special class of common stock, Class T common stock, the LTBT generally has the authority to elect and remove the Class T directors, who together will constitute a majority of the authorized members of our board of directors. The Our Class T common stock does not otherwise have voting rights on matters submitted to stockholders generally.

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The Our Class F common stock will be entitled to an aggregate number of votes that equals 50.1% of the total voting power of our outstanding shares of capital stock with respect to matters submitted to stockholders generally, including the election of our directors other than the Class T directors.

Decisions regarding our business and affairs are made by our board of directors. Immediately prior to the completion of this offering, we will enter into a stockholders agreement (the Stockholders Agreement ) with the LTBT and the Founder LLC, under which they will agree to vote their shares and take other actions to give effect to the board composition, director nomination, and director removal provisions described in our governing documents. Collectively, the LTBT and the Founder LLC will have the ability to elect all members of our board of directors. Regardless of the class or classes of stock by which a director is elected, there is no limit to the number of terms a director may serve.

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The Founder LLC will also have significant influence over our business and affairs through its ability to vote the our Class F common stock, which is entitled to an aggregate number of votes that equals 50.1% of the total voting power of our outstanding shares of capital stock with respect to matters submitted to stockholders generally, including the election of our directors other than the Class T directors.

See the sections titled Risk Factors Risks Related to our Governance Structure, Our Governance Structure and Its Goals, Management, Certain Relationships and Related Person Transactions, and Description of Capital Stock for more information.

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The following table summarizes certain key terms of each class or series of our common stock that will be authorized following the completion of this offering Category of Rights Class A Common Stock Class N Common Stock Class T Common Stock Class F Common Stock Class E Common Stock Votes per share 50.1% of outstanding voting power on record date Matters on which entitled to vote All matters submitted to stockholders generally election of non-Class T directors certain amendments to the terms of the LTBT or the rights of the our Class T common stock redemption of the our Class T common stock Not entitled to vote except as required by law, in which case the our Class N common stock will have one vote per share Election of Class T directors, which constitute a majority of our board of directors redemption of the our Class E common stock certain amendments to the rights of the our Class F common stock All matters submitted to stockholders generally election of non-Class T directors certain amendments to the terms of the LTBT or the rights of the our Class T common stock redemption of the our Class T common stock redemption of the our Class E common stock Nomination, change in designation, or removal of the Specified Class T Director (as defined below) (only if our NGC does not concur in the LTBT s nomination, change in designation, or removal) certain amendments to the terms of the LTBT or the rights of the our Class T common stock redemption of the our Class T common stock Conversion rights None Converts into Class A common stock upon a sale or transfer to an unaffiliated third party None None None Transferability Generally transferable Generally transferable converts to Class A common stock upon transfer as described above Transferable only upon approval of persons comprising the Trust Amendment Threshold (as defined below) Not transferable except in the case of a reorganization or redomiciliation of the Founder LLC that is approved by our board of directors and does not result in a change to the members of the Founder LLC Not transferable Dividend rights Entitled to participate pro rata in dividends and distributions Entitled to participate pro rata in dividends and distributions None None None Right to receive liquidation distributions Entitled to participate pro rata in liquidation distributions Entitled to participate pro rata in liquidation distributions Entitled to par value per share Entitled to par value per share Entitled to par value per share Redeemable by company No No Redeemable by us for no consideration upon occurrence of certain events Redeemable by us for no consideration upon occurrence of certain events Redeemable by us for no consideration upon occurrence of certain events For more information about our capital structure, see the section titled Description of Capital Stock.

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See the section titled Risk Factors and other information

included in this prospectus for a discussion of some of the

factors you should consider before deciding to invest in our

Class A common stock.

Proposed trading symbol

The number of shares of our Class A common stock, Class N common stock, Class T common stock, and Class F common stock that will be outstanding after this offering is based on shares of our Class A common stock, shares of our Class N common stock, one share of our Class T common stock, and one share of our Class F common stock outstanding as of September 30, 2026, which reflects the automatic conversion of (i) all outstanding shares of our Series A, C-1, D-1, D-2, E-1, F-1, G-1, and H-1 redeemable convertible preferred stock into shares of Class A common stock and (ii) all outstanding shares of our Series B, C-2, D-3, E-2, E-3, E-4, E-5, F-2, G-2, G-3, G-4, H-2, H-3, and H-4 redeemable convertible preferred stock into shares of Class N common stock, immediately prior to the completion of this offering pursuant to the terms of our amended and restated certificate of incorporation (collectively, the Preferred Stock Conversion ) one share of our Class F common stock that will be issued immediately prior to the completion of this offering to the Founder LLC (the Class F Stock Issuance ) the conversion of $ in aggregate principal amount of our outstanding convertible promissory notes into shares of Class N common stock immediately prior to the completion of this offering, representing shares issuable to Amazon Web Services, Inc. upon the completion of this offering without causing it to exceed the applicable ownership cap (the the Initial Public Benefit Issuance, the shares of which (i) are considered legally outstandin g, (ii) are not considered outstanding for accounting purposes while held by our wholly owned subsidiary, and (iii) accordingly will not be reflected as outstanding in our consolidated financial statements and the net issuance of shares of Class A common stock subject to RSUs for which the service-based vesting condition was satisfied as of the date of this prospectus and the performance-based vesting condition will be satisfied upon the effectiveness of the registration statement of which this prospectus forms a part, after giving effect to the withholding of shares of Class A common stock subject to such RSUs to satisfy the associated estimated tax withholding and remittance obligations (based upon the assumed initial public offering price of $ per share, which is the midpoint of the estimated offering price range set forth on the cover page of this prospectus, and an assumed % tax withholding rate) (the RSU Settlement ).

The shares of our Class A common stock, Class N common stock, Class T common stock, and Class F common stock outstanding as of September 30, 2026 exclude the following shares of our Class A common stock issuable upon the exercise of options to purchase shares of our Class A common stock outstanding as of September 30, 2026, with a weighted-average exercise price of $ per share shares of our Class A common stock issuable upon the vesting and settlement of RSUs outstanding as of the date of this prospectus, but for which (i) the service-based vesting condition was not satisfied as of such date and (ii) the performance-based vesting condition, if applicable, will be satisfied upon the effectiveness of the registration statement of which this prospectus forms a part shares of our Class A common stock issued after September 30, 2026 in connection with our acquisitions of privately-held companies and shares of our Class A common stock reserved for future issuance under our equity compensation plans, consisting of shares of our Class A common stock reserved for future issuance upon conversion of Class N common stock issuable under our Donation Matching Plan (as amended and restated, the shares of our Class A common stock to be reserved for future issuance under our 2026 Equity Incentive Plan (our 2026 Plan ), which will become effective prior to the completion of this offering shares of our Class A common stock reserved for future issuance under our Amended and Restated 2021 Stock Plan (our 2021 Plan ) as of September 30, 2026, which number of shares will be added to the shares of our Class A common stock to be reserved for future issuance under our 2026 Plan upon its effectiveness, at which time we will cease granting awards under our 2021 Plan and shares of our Class A common stock to be reserved for future issuance under our 2026 Employee Stock Purchase Plan (our ESPP ), which will become effective prior to the completion of this offering.

Our 2026 Plan and ESPP each provide for an annual automatic increase in the number of shares of our Class A common stock reserved thereunder, and our 2026 Plan provides for increases to the number of shares that may be granted thereunder based on awards under our 2021 Plan that expire or are cancelled or forfeited, and shares under our 2021 Plan that are tendered to or withheld by us for payment of an exercise price or for satisfying tax withholding obligations or are forfeited or otherwise repurchased by us, as more fully described in the section titled Executive Compensation Equity Plans .

Except as otherwise indicated, all information in this prospectus assumes the Preferred Stock Conversion will occur immediately prior to the completion of this offering the Convertible Notes Conversion will occur immediately prior to the completion of this offering the filing and effectiveness of our amended and restated certificate of incorporation in Delaware and the effectiveness of our amended and restated bylaws will each occur immediately prior to the completion of this offering the Class F Stock Issuance will occur immediately prior to the completion of this offering no issuance of shares of Class E common stock prior to the completion of this offering a 10-for-one forward split of our Class A common stock and Class N common stock effected on September 17, 2026, including a proportional increase in the authorized shares of our capital stock, with all share, option, RSU, and per share information for all periods presented in this prospectus adjusted to reflect such forward split on a retroactive basis a one-for-1,000 reverse split of our Class T common stock effected on September 17, 2026 no exercise of outstanding stock options or settlement of outstanding RSUs subsequent to September 30, 2026, other than the RSU Settlement and no exercise by the underwriters of their option to purchase up to an additional shares of our Class A common stock from us in this offering.

Summary Consolidated Financial and Other Data

The following tables summarize our consolidated financial and other data. We have derived the summary consolidated statements of operations data for the years ended December 31, 2023, 2024, and 2025 from our audited consolidated financial statements included elsewhere in this prospectus. We have derived the summary consolidated statements of operations data for the six months ended June 30, 2025 and 2026 , and the summary consolidated balance sheet data as of June 30, 2026, from our unaudited interim consolidated financial statements included elsewhere in this prospectus. The summary consolidated financial data in this section are not intended to replace our consolidated financial statements and related notes and are qualified in their entirety by our consolidated financial statements and related notes included elsewhere in this prospectus.

Our historical results are not necessarily indicative of the results that may be expected in the future and our results for the six months ended June 30, 2026 are not necessarily indicative of the results that may be expected for the full year ending December 31, 2026 or any other period. The following summary consolidated financial and other data should be read in conjunction with the section titled Management s Discussion and Analysis of Financial Condition and Results of Operations and our consolidated financial statements and related notes thereto included elsewhere in this prospectus.

Consolidated Statements of Operations Data

Year Ended December 31,

Six Months Ended June 30,

(in millions, except share and per share

Compute and infrastructure

Sales, marketing, and partnerships

Other operating and administrative

Total operating expenses

Change in fair value of convertible

notes, derivative liabilities, and SAFEs

Other income (expense), net

Total other income (expense), net

Loss before provision for income taxes

Provision for income taxes

Net loss per share attributable to common

stockholders, basic and diluted

Weighted-average number of shares

outstanding, basic and diluted

(1) Includes stock-based compensation expense of $29 million , $192 million , and $1.2 billion for the years ended December 31, 2023, 2024, and 2025, respectively, and $286 million and $2.2 billion for the six months ended June 30, 2025 and 2026, respectively.

(2) Includes change in fair value of convertible notes, derivative liabilities, and simple agreements for future equity ( SAFEs ), which were $1.0 billion , $5.4 billion , and $34.3 billion for the years ended December 31, 2023, 2024, and 2025, respectively, and $10.9 billion and $72.4 billion for the six months ended June 30, 2025 and 2026, respectively. These changes were primarily driven by an increase in the fair value of our outstanding convertible promissory notes resulting from an increase in our enterprise valuation during each of the respective periods.

The following table sets forth the computation of unaudited pro forma net loss per share, basic and diluted, of common stock attributable to common stockholders for the periods presented (in millions, except share and per share amounts) Year Ended December 31, 2025 Six Months Ended June 30, 2026 Numerator Net loss $ (41,965) $ (80,748) Pro forma adjustment to record stock-based compensation expense related to RSUs for which the performance-based vesting condition will be satisfied upon the effectiveness of the registration statement of which this prospectus forms a part Pro forma adjustment to eliminate the change in fair value recognized related to the Convertible Notes Conversion Pro forma net loss Denominator Weighted-average number of shares outstanding, basic and diluted 1,821,084,860 2,024,972,990 Pro forma adjustment to reflect the Preferred Stock Conversion Pro forma adjustment to reflect the RSU Settlement Pro forma adjustment to reflect the Convertible Notes Conversion Weighted-average number of shares outstanding used to compute pro forma net loss per share, basic and diluted (1)(2) Pro forma net loss per share, basic and diluted (1)(2) ______________ (1) The unaudited pro forma net loss per share and pro forma weighted-average number of shares used in computing pro forma net loss per share give effect to (i) the Preferred Stock Conversion, as if such conversion had occurred on January 1, 2025 , (ii) the Convertible Notes Conversion, as if such conversion had occurred on January 1, 2025, (iii) stock-based compensation expense related to RSUs for which the service-based vesting condition was satisfied or partially satisfied, and as if the performance condition had been satisfied on January 1, 2025, of $ and $ for the year ended December 31, 2025 and the six months ended June 30, 2026, respectively, (iv) the net issuance of and shares of our Class A common stock upon the vesting and settlement of RSUs, for which the service-based vesting condition was satisfied, and as if the performance condition had been satisfied on January 1, 2025, for the year ended December 31, 2025 and the six months ended June 30, 2026, respectively, and (v) the filing and effectiveness of our amended and restated certificate of incorporation in Delaware that will become effective immediately prior to the completion of this offering. The pro forma weighted-average number of shares does not give effect to the Initial Public Benefit Issuance, as shares of our Class N common stock held by our wholly owned subsidiary are not considered outstanding for accounting purposes.

(2) As of , 2026, unrecognized stock-based compensation expense not reflected in pro forma net loss per share was $ related to RSUs for which the service-based vesting condition was not satisfied, and which is expected to be recognized over a weighted-average period of approximately years, and $ related to our other outstanding equity awards, which is expected to be recognized over a weighted-average period of approximately years.

Consolidated Balance Sheet Data

Cash, cash equivalents, and short-term investments

Redeemable convertible preferred stock

Additional paid-in capital

Total stockholders deficit

(1) The pro forma column in the consolidated balance sheet gives effect to (i) the Preferred Stock Conversion, as if such conversion had occurred on June 30, 2026, (ii) the Convertible Notes Conversion, as if such conversion had occurred on June 30, 2026, (iii) the Class F Stock Issuance, as if it had occurred on June 30, 2026, (iv) an increase to additional paid-in capital and accumulated deficit related to stock-based compensation of $ related to RSUs subject to the RSU Settlement, and (v) the filing and effectiveness of our amended and restated certificate of incorporation in Delaware that will become effective immediately prior to the completion of this offering.

(2) The pro forma as adjusted column gives effect to (i) the pro forma adjustments set forth above, (ii) the sale and issuance b y us of shares of our Class A common stock in this offering, based upon the assumed initial public offering price of $ per share, which is the midpoint of the estimated price range set forth on the cover page of this prospectus, and after deducting estimated underwriting discounts and commissions and estimated offering expenses payable by us, and (iii) the use of net proceeds from this offering, together with existing cash and cash equivalents, if necessary, to satisfy the estimated tax withholding and remittance obligations related to the RSU Settlement. We will not receive any proceeds from the sale of shares of our Class A common stock by any of the selling stockholders.

(3) Each $1.00 increase (decrease) in the assumed initial public offering price would increase (decrease) each of cash, cash equivalents, and short-term investments working capital total assets additional paid-in capital and total stockholders deficit by $ , assuming the number of shares offered by us as stated on the cover page of this prospectus remains unchanged and after deducting the estimated underwriting discounts and commissions and estimated offering expenses payable by us.

Similarly, an increase (decrease) of 1.0 million shares in the number of shares offered by us, as set forth on the cover page of this prospectus, would increase (decrease) each of cash, cash equivalents, and short-term investments working capital total assets additional paid-in capital and total stockholders deficit by $ , assuming the assumed initial public offering price of $ per share (the midpoint of the price range set forth on the cover page of this prospectus) remains the same, and after deducting the estimated underwriting discounts and commissions and estimated offering expenses payable by us. We will not receive any proceeds from the sale of shares of our Class A common stock by any of the selling stockholders.

(4) Working capital is defined as current assets less current liabilities.

Non-GAAP Financial Measures

In addition to the measures presented in our consolidated financial statements that were prepared in accordance with accounting principles generally accepted in the United States ( GAAP ), we use Adjusted Operating Income (Loss), Adjusted Operating Margin, and Adjusted Net Income (Loss) as non-GAAP financial measures to evaluate our business, measure our performance, identify trends affecting our business, formulate business plans, and make strategic decisions.

Year Ended December 31,

Six Months Ended June 30,

(in millions, except for percentages)

Adjusted Operating Income (Loss)

and 3 more changes in the filing

Risk factors 115 changes

See the section titled Risk Factors and other information

included in this prospectus for a discussion of some of the

factors you should consider before deciding to invest in our

Class A common stock.

Proposed trading symbol

The number of shares of our Class A common stock, Class N common stock, Class T common stock, and Class F common stock that will be outstanding after this offering is based on shares of our Class A common stock, shares of our Class N common stock, one share of our Class T common stock, and one share of our Class F common stock outstanding as of June 30, 2026, which reflects the automatic conversion of (i) all outstanding shares of our Series A, C-1, D-1, D-2, E-1, F-1, G-1, and H-1 redeemable convertible preferred stock into shares of Class A common stock and (ii) all outstanding shares of our Series B, C-2, D-3, E-2, E-3, E-4, E-5, F-2, G-2, G-3, G-4, H-2, H-3, and H-4 redeemable convertible preferred stock into shares of Class N common stock, immediately prior to the completion of this offering pursuant to the terms of our amended and restated certificate of incorporation (collectively, the Preferred Stock Conversion ) one share of our Class F common stock that will be issued immediately prior to the completion of this offering to the Founder LLC (the Class F Stock Issuance ) the conversion of $ in aggregate principal amount of our outstanding convertible promissory notes into shares of Class N common stock immediately prior to the completion of this offering, representing shares issuable to Amazon Web Services, Inc. upon the completion of this offering without causing it to exceed the applicable ownership cap (the the Initial Public Benefit Issuance, the shares of which will be considered legally outstanding, will not be considered outstanding for accounting purposes while held by our wholly owned subsidiary, and accordingly will not be reflected as outstanding in our consolidated financial statements and the net issuance of shares of Class A common stock subject to RSUs for which the service-based vesting condition was satisfied as of the date of this prospectus and the performance-based vesting condition will be satisfied upon the effectiveness of the registration statement of which this prospectus forms a part, after giving effect to the withholding of shares of Class A common stock subject to such RSUs to satisfy the associated estimated tax withholding and remittance obligations (based upon the assumed initial public offering price of $ per share, which is the midpoint of the estimated offering price range set forth on the cover page of this prospectus, and an assumed % tax withholding rate) (the RSU Settlement ).

The shares of our Class A common stock, Class N common stock, Class T common stock, and Class F common stock outstanding as of June 30, 2026 exclude the following 1,797,066,050 shares of our Class A common stock issuable upon the exercise of options to purchase shares of our Class A common stock outstanding as of June 30, 2026, with a weighted-average exercise price of $2.89 per share shares of our Class A common stock issuable upon the exercise of options to purchase shares of our Class A common stock granted after June 30, 2026, with a weighted-average exercise price of shares of our Class A common stock issuable upon the vesting and settlement of RSUs outstanding as of the date of this prospectus, but for which (i) the service-based vesting condition was not satisfied as of such date and (ii) the performance-based vesting condition, if applicable, will be satisfied upon the effectiveness of the registration statement of which this prospectus forms a part shares of our Class A common stock reserved for future issuance under our equity compensation plans, consisting of shares of our Class A common stock reserved for future issuance upon conversion of Class N common stock issuable under our Donation Matching Plan (as amended and restated, the shares of our Class A common stock to be reserved for future issuance under our 2026 Equity Incentive Plan ( 2026 Plan ), which will become effective prior to the completion of this offering shares of our Class A common stock reserved for future issuance under our Amended and Restated 2021 Stock Plan ( 2021 Plan ) as of June 30, 2026, which number of shares will be added to the shares of our Class A common stock to be reserved for future issuance under our 2026 Plan upon its effectiveness, at which time we will cease granting awards under our 2021 Plan and shares of our Class A common stock to be reserved for future issuance under our 2026 Employee Stock Purchase Plan ( ESPP ), which will become effective prior to the completion of this offering.

Our 2026 Plan and ESPP each provide for an annual automatic increase in the number of shares of our Class A common stock reserved thereunder, and our 2026 Plan provides for increases to the number of shares that may be granted thereunder based on awards under our 2021 Plan that expire or are cancelled or forfeited, and shares under our 2021 Plan that are tendered to or withheld by us for payment of an exercise price or for satisfying tax withholding obligations or are forfeited or otherwise repurchased by us, as more fully described in the section titled Executive Compensation Equity Plans .

Except as otherwise indicated, all information in this prospectus assumes the Preferred Stock Conversion will occur immediately prior to the completion of this offering the Convertible Notes Conversion will occur immediately prior to the completion of this offering the filing and effectiveness of our amended and restated certificate of incorporation in Delaware and the effectiveness of our amended and restated bylaws will each occur immediately prior to the completion of this offering the Class F Stock Issuance will occur immediately prior to the completion of this offering no issuance of shares of Class E common stock prior to the completion of this offering a 10-for-one forward split of our Class A common stock and Class N common stock effected on September 17, 2026, including a proportional increase in the authorized shares of our capital stock, with all share, option, RSU, and per share information for all periods presented in this prospectus adjusted to reflect such forward split on a retroactive basis a one-for-1,000 reverse split of our Class T common stock effected on September 17, 2026 no exercise of outstanding stock options or settlement of outstanding RSUs subsequent to June 30, 2026, other than the RSU Settlement and no exercise by the underwriters of their option to purchase up to an additional shares of our Class A common stock from us in this offering.

Summary Consolidated Financial and Other Data

The following tables summarize our consolidated financial and other data. We have derived the summary consolidated statements of operations data for the years ended December 31, 2023, 2024, and 2025 from our audited consolidated financial statements included elsewhere in this prospectus. We have derived the summary consolidated statements of operations data for the six months ended June 30, 2025 and 2026 , and the summary consolidated balance sheet data as of June 30, 2026, from our unaudited interim consolidated financial statements included elsewhere in this prospectus. The summary consolidated financial data in this section are not intended to replace our consolidated financial statements and related notes and are qualified in their entirety by our consolidated financial statements and related notes included elsewhere in this prospectus.

Our historical results are not necessarily indicative of the results that may be expected in the future and our results for the six months ended June 30, 2026 are not necessarily indicative of the results that may be expected for the full year ending December 31, 2026 or any other period. The following summary consolidated financial and other data should be read in conjunction with the section titled Management s Discussion and Analysis of Financial Condition and Results of Operations and our consolidated financial statements and related notes thereto included elsewhere in this prospectus.

Consolidated Statements of Operations Data

Year Ended December 31,

Six Months Ended June 30,

(in millions, except share and per share

Compute and infrastructure

Sales, marketing, and partnerships

Other operating and administrative

Total operating expenses

Change in fair value of convertible

notes, derivative liabilities, and SAFEs

Other income (expense), net

Total other income (expense), net

Loss before provision for income taxes

Provision for income taxes

Net loss per share attributable to common

Weighted-average number of shares

outstanding, basic and diluted

The following table sets forth the computation of unaudited pro forma net loss per share, basic and diluted of common stock attributable to common stockholders for the periods presented (in millions, except share and per share amounts) Year Ended December 31, 2025 Six Months Ended June 30, 2026 Numerator Net loss $ (41,965) $ (80,748) Pro forma adjustment to record stock-based compensation expense related to RSUs for which the performance-based vesting condition will be satisfied upon the effectiveness of the registration statement of which this prospectus forms a part Pro forma adjustment to eliminate the change in fair value recognized related to the Convertible Notes Conversion Pro forma net loss Denominator Weighted-average number of shares outstanding, basic and diluted 1,821,084,860 2,024,972,990 Pro forma adjustment to reflect the Preferred Stock Conversion Pro forma adjustment to reflect the RSU Settlement Pro forma adjustment to reflect the Convertible Notes Conversion Weighted-average number of shares outstanding used to compute pro forma net loss per share, basic and diluted (3)(4) Pro forma net loss per share, basic and diluted (3)(4) ______________ (1) Includes stock-based compensation expense of $29 million , $192 million , and $1.2 billion for the years ended December 31, 2023, 2024, and 2025, respectively, and $286 million and $2.2 billion for the six months ended June 30, 2025 and 2026, respectively.

(2) Includes change in fair value of convertible notes, derivative liabilities, and simple agreements for future equity ( SAFEs ), which were $1.0 billion , $5.4 billion , and $34.3 billion for the years ended December 31, 2023, 2024, and 2025, respectively, and $10.9 billion and $72.4 billion for the six months ended June 30, 2025 and 2026, respectively. These changes were primarily driven by an increase in the fair value of our outstanding convertible promissory notes resulting from an increase in our enterprise valuation during each of the respective periods.

(3) The pro forma weighted-average number of shares used in computing pro forma net loss per share gives effect to (i) the Preferred Stock Conversion, as if such conversion had occurred on January 1, 2025 , (ii) the Convertible Notes Conversion, as if such conversion had occurred on January 1, 2025, (iii) stock-based compensation expense related to RSUs for which the service-based vesting condition was satisfied or partially satisfied, and as if the performance condition had been satisfied on January 1, 2025, of $ and $ for the year ended December 31, 2025 and the six months ended June 30, 2026, respectively, and (iv) the filing and effectiveness of our amended and restated certificate of incorporation in Delaware that will become effective immediately prior to the completion of this offering. The pro forma weighted-average number of shares does not give effect to the Initial Public Benefit Issuance, as shares of our Class N common stock held by our wholly owned subsidiary are not considered outstanding for accounting purposes.

(4) As of , 2026, unrecognized stock-based compensation expense not reflected in pro forma net loss per share was $ related to RSUs for which the service-based vesting condition was not satisfied, and which is expected to be recognized over a weighted-average period of approximately years, and $ related to our other outstanding equity awards, which is expected to be recognized over a weighted-average period of approximately years.

Consolidated Balance Sheet Data

Cash, cash equivalents, and short-term investments

Redeemable convertible preferred stock

Additional paid-in capital

Total stockholders deficit

(1) The pro forma column in the consolidated balance sheet gives effect to (i) the Preferred Stock Conversion, as if such conversion had occurred on June 30, 2026, (ii) the Convertible Notes Conversion, as if such conversion had occurred on June 30, 2026, (iii) the Class F Stock Issuance, as if it had occurred on June 30, 2026, (iv) an increase to additional paid-in capital and accumulated deficit related to stock-based compensation of $ related to RSUs subject to the RSU Settlement, and (v) the filing and effectiveness of our amended and restated certificate of incorporation in Delaware that will become effective immediately prior to the completion of this offering.

(2) The pro forma as adjusted column gives effect to (i) the pro forma adjustments set forth above, (ii) the sale and issuance b y us of shares of our Class A common stock in this offering, based upon the assumed initial public offering price of $ per share, which is the midpoint of the estimated price range set forth on the cover page of this prospectus, and after deducting estimated underwriting discounts and commissions and estimated offering expenses payable by us, and (iii) the use of net proceeds from this offering, together with existing cash and cash equivalents, if necessary, to satisfy the estimated tax withholding and remittance obligations related to the RSU Settlement. We will not receive any proceeds from the sale of shares of our Class A common stock by any of the selling stockholders.

(3) Each $1.00 increase (decrease) in the assumed initial public offering price would increase (decrease) each of cash, cash equivalents, and short-term investments working capital total assets additional paid-in capital and total stockholders deficit by $ , assuming the number of shares offered by us as stated on the cover page of this prospectus remains unchanged and after deducting the estimated underwriting discounts and commissions and estimated offering expenses payable by us.

Similarly, an increase (decrease) of 1.0 million shares in the number of shares offered by us, as set forth on the cover page of this prospectus, would increase (decrease) each of cash, cash equivalents, and short-term investments working capital total assets additional paid-in capital and total stockholders deficit by $ , assuming the assumed initial public offering price of $ per share (the midpoint of the price range set forth on the cover page of this prospectus) remains the same, and after deducting the estimated underwriting discounts and commissions and estimated offering expenses payable by us. We will not receive any proceeds from the sale of shares of our Class A common stock by any of the selling stockholders.

(4) Working capital is defined as current assets less current liabilities.

Non-GAAP Financial Measures

In addition to the measures presented in our consolidated financial statements that were prepared in accordance with accounting principles generally accepted in the United States ( GAAP ), we use Adjusted Operating Income (Loss), Adjusted Operating Margin, and Adjusted Net Income (Loss) as non-GAAP financial measures to evaluate our business, measure our performance, identify trends affecting our business, formulate business plans, and make strategic decisions.

Year Ended December 31,

Six Months Ended June 30,

(in millions, except for percentages)

Adjusted Operating Income (Loss)

Adjusted Operating Margin

Adjusted Net Income (Loss)

See the section titled Management s Discussion and Analysis of Financial Condition and Results of Operations Non-GAAP Financial Measures for a definition of each non-GAAP financial measure, a discussion of the limitations of each non-GAAP financial measure, and a reconciliation of each non-GAAP financial measure to its most comparable GAAP financial measure for the periods presented and additional information.

If any of the risks actually occur, our business, financial condition, results of operations, and prospects could be adversely affected. In that event, the market price of our Class A common stock could decline, and you could lose part or all of your investment.

Investing in our Class A common stock involves a high degree of risk. You should carefully consider the risks and uncertainties described below, together with all of the other information in this prospectus, including the section titled Management s Discussion and Analysis of Financial Condition and Results of Operations and our consolidated financial statements and related notes, before making a decision to invest in our Class A common stock. The disclosures in this section reflect our beliefs and opinions as to matters that could materially and adversely affect us in the future, and are not representations as to whether such matters have or have not occurred previously, except as otherwise disclosed. References to past events are provided by way of example only and are not intended to be a complete listing or a representation as to their likelihood of occurring in the future. Our business, financial condition, results of operations, or prospects could also be adversely affected by risks and uncertainties not currently known to us or that we currently do not believe are material. If any of the risks actually occur, our business, financial condition, results of operations, and prospects could be adversely affected. In that event, the market price of our Class A common stock could decline, and you could lose part or all of your investment.

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In addition, innovation in AI involves addressing complex and evolving challenges related to data quality, training methodologies, bias, safety, accuracy, and the behavior of model outputs. AI algorithms may be flawed, and AI systems may fail to follow instructions or produce inaccurate, misleading, offensive, inappropriate, or otherwise harmful outputs reflect or amplify unwanted or unknown biases present in training data or raise concerns relating to intellectual property, privacy, or other legal and ethical considerations. We must continually invest resources to identify, mitigate, remediate, and reduce the occurrence of such issues, including through improved datasets, training techniques, evaluation methods, safeguards, and human oversight.

In addition, innovation in AI involves addressing complex and evolving challenges related to data quality, data integrity, training methodologies, bias, safety, accuracy, and the behavior of model outputs. AI algorithms may be flawed, and AI systems may contain bugs, errors, or defects or fail to follow instructions or produce inaccurate, misleading, offensive, inappropriate, or otherwise harmful outputs reflect or amplify unwanted or unknown biases present in training data or raise concerns relating to intellectual property, privacy, or other legal and ethical considerations. We must continually invest resources to identify, mitigate, remediate, and reduce the occurrence of such issues, including through managing and improving datasets, training techniques, evaluation methods, safeguards, and human oversight. However, we may not be able to obtain the datasets that we need, including through licenses or strategic data partnerships. In addition, we or our data providers may use synthetic or AI-generated data in the training process, which could introduce quality issues, amplify biases or errors, contribute to model degradation, or raise novel legal questions regarding ownership, licensing, or intellectual property rights that may not be timely or clearly resolved by courts or regulators. Such unintended consequences, failures, or misuse of our models could impair customer trust, slow adoption, expose us to legal or regulatory scrutiny, or adversely affect our brand and reputation.

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The majority of our compute is procured under multi-year commitments that are typically entered into well in advance of the periods in which that compute is deployed. Because different AI accelerators have varying performance characteristics across workload types, the composition of our committed compute portfolio, including the mix of accelerator architectures procured from our partners, reflects our demand forecasts and development roadmap assumptions at the time those commitments are made. If the magnitude or mix of workloads we need to support differs materially from those forecasts, whether due to changes in model architecture, customer demand, internal operations, or research priorities, the composition of our available compute may not optimally match our needs in a given period. This could affect our ability to serve customers, develop models, and support internal operations.

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We have entered into, and expect to continue to enter into, long-term agreements for compute and other compute resources that involve minimum purchase commitments, take-or-pay provisions, and other terms that obligate us to pay for resources regardless of actual utilization. These commitments represent substantial fixed obligations. As of , our aggregate committed spend under and subsequent to September 30, 2026, we have entered into purchase commitments and lease agreements, was including short-term commitments, as well as leases not yet commenced, with an aggregate committed spend of more than $ , substantially all of which is related to compute and infrastructure. and we expect These commitments will continue include approximately $ expected to increase. be incurred before December 31, 2030, and substantially all of the remainder is expected to be incurred between 2031 and 2045. Approximately $ of these commitments are due in the next 12 months. See the section titled Management s Discussion and Analysis of Financial Condition and Results of Operations Liquidity and Capital Resources Contractual Obligations for more information.

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Even where chips and electrical power are available, the development of data center facilities requires substantial time, capital, and specialized expertise. Data center construction involves lengthy permitting processes, complex supply chains for specialized equipment, and significant lead times for the installation and commissioning of cooling systems, electrical infrastructure, and networking equipment. Labor shortages, including shortages of, and competition for, electricians, facility technicians, and other skilled tradespeople, supply chain disruptions, permitting delays, and other factors can extend construction timelines and increase costs . Further, given data center development projects require advanced and significant capital commitments with dedicated end users, we may have in some cases relied, and expect to continue to rely, on arrangements for financing or with partners who guarantee the lease obligations to support the development of data center capacity that is expected to host such partner s chips or computing infrastructure. In addition, there are a limited number of qualified third-party vendors with the expertise we require and that support the particular infrastructure we wish to implement. Accordingly, we rely on this limited number of third parties for the construction, management, and operation of certain of our data center facilities, some of which have limited operating history or may have less experience operating data center infrastructure at the scale and complexity our operations require. In certain cases, these third-party operators are trained or supervised by our chip partners to manage facilities on our behalf but are not affiliates of those partners and may not have the same depth of expertise, operational resilience, or resources. Any failure by these third-party operators to perform as expected could disrupt our access to compute. In addition, safety or environmental incidents at facilities built or operated for us, whatever their cause, could expose us to claims, fines, or suspensions of construction or operations, the costs of which we may bear. We also depend on an extended network of suppliers, builders, and facility operators. If any of them engage in practices that are unsafe, unlawful, or contrary to the labor, human rights, environmental, or other standards we or our partners require, we could face legal liability, lose the ability to use affected suppliers or facilities, and suffer harm to our reputation, even where we did not direct or know of the conduct.

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We compete directly with companies developing frontier models for third-party software developers and enterprises. Our primary competitors in this category include Alphabet Inc. ( (together with its affiliates, Google ) and OpenAI Group PBC ( OpenAI ). These competitors are developing increasingly capable AI systems and compete with us for customers, talent, compute, and strategic partnerships. Many have substantially greater financial, technical, and marketing resources than we do, their own or greater access to sources of compute, longer operating histories, greater brand recognition, and established relationships with current and potential customers and partners, which facilitates their ability to integrate their models into first-party first- party applications sold directly to businesses.

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For example, in September 2025, we detected and assessed with high confidence that a Chinese state-sponsored hacking group manipulated our Claude Code tool into attempting infiltration into roughly 30 global targets, including large technology companies, financial institutions, chemical manufacturing companies, and government agencies, resulting in a limited number of successful intrusions. We believe this is the first documented case of a large-scale cyberattack executed without substantial human intervention. We expect that malicious actors, including sophisticated state-sponsored actors, will continue to seek to leverage our models, platform, and applications for harmful actions, including by circumventing our safeguards, and their efforts to do so may increase as the capabilities of our technology increase. Any successful attempt to misuse, or any perceived misuse of, our models, platform, and applications for a cyberattack or for any other malicious purpose could result in exposure to liability, disruption of our customer or other commercial relationships, or damage to our reputation. The risks of such harms may increase as the cybersecurity-related capabilities of our models, platform, and applications increase. Independent security researchers and other third parties have also used, and may in the future use, our models to identify and exploit vulnerabilities in the systems of other companies, including other AI developers, at times in connection with authorized bug bounty programs. While such activity may be lawful and consistent with industry practice for vulnerability research, it illustrates that our models can function as a general-purpose tool for gaining unauthorized access to third-party systems, and comparable capabilities could be used by malicious actors without authorization. Such incidents, whether or not we are a direct party to them, may draw public and regulatory attention to the offensive cybersecurity capabilities of our models and could result in reputational harm, calls for additional restrictions on our models, or claims that we failed to adequately safeguard against such uses. For example, in September 2026, media reports citing a senior Federal Trade Commission ( FTC ) official indicated that the FTC has opened an industry-wide, non-public investigation into the potential risks that increasingly autonomous AI systems pose to consumers, reportedly focused in part on an incident in which AI agents developed by another company in our industry were used to gain unauthorized access to a third-party platform, and reportedly intends to issue civil investigative demands and seek testimony from executives at several AI developers, including us. For more information regarding this investigation, see the section titled If we are unable to manage the risks related to our focus on and commitment to AI safety, our brand, business, financial condition, and results of operations could be adversely affected. Additionally, state attorneys general in California and Florida have also announced investigations of another company in our industry regarding AI safety. For more information about risks related to security incidents, see the section titled Any security breaches or other incidents, including those that affect our networks, systems, or data, or the networks, systems, or data of our service providers, suppliers, or customers, could adversely affect our business, financial condition, and results of operations.

As part of our commitment to responsible security research and transparency, we disclose information about the capability and safety of our models, the safeguards that we have adopted with respect to our models, and instances of misuse of our technology, such as the September 2025 cyberattack described above. We also publish model system cards, our research findings, and other safety-related information. We take steps to ensure that such disclosures will not materially assist malicious activity and weigh the benefits and risks of such disclosures from an ecosystem preparedness perspective however, malicious actors, including sophisticated state-sponsored adversaries, have in the past and may in the future use those disclosures to assist their attempts to circumvent our safeguards and security measures, thereby increasing the risks of misuse of our models, platform, and applications, as well as the potential for exposure to liability, regulatory or litigation proceedings, or other harms. In addition, because these disclosures describe risks and observed model behaviors in detail, they may draw heightened public, media, or regulatory attention and could be cited by regulators, litigants, or others in proceedings or claims against us. The steps we take to prevent misuse of our models, platform, and applications are could be incomplete or may fail to operate as intended, and any actual or perceived misuse could adversely affect our business, financial condition, and results of operations.

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Our development of more advanced AI models and our expansion into new jurisdictions could amplify the foregoing risks. As our AI models become more advanced and capable, we have faced and may continue to face heightened alignment, interpretability, controllability, and safety challenges, as more sophisticated models may be better able to circumvent safeguards or behave in unintended ways. We may be unable to fully understand or explain why our models produce particular outputs or behave in particular ways, which could limit our ability to predict or prevent failures, provide explanations to customers or regulators, or satisfy emerging regulatory, transparency, and explainability requirements.

In addition, our safety evaluations and testing processes have produced and may in the future produce incomplete or unreliable results. One potential cause is that For example, we have observed models may behave behaving differently when they detect or infer that they are being evaluated, which can limit our ability to accurately assess real-world risks or failure modes prior to deployment. Potential Such model awareness of our evaluation efforts creates a significant limitation on our ability to assess model safety.

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In addition, advanced AI models, including our models, give rise to novel ethical and safety risks, including risks related to autonomy, manipulation, and the simulation of aspects of human psychology. These risks could result in unforeseen harms and may require the development of governance structures, safeguards, or mitigation strategies beyond existing AI safety frameworks, and there is always a risk that we will be unable to develop or implement them effectively. In addition, models, including our own, have exhibited, and may in the future exhibit, unexpected strategic or self-preserving behaviors, including attempts to resist shutdown, conceal or manipulate information, or generate outputs that could be interpreted as coercive, deceptive, or manipulative, including behavior resembling blackmail or efforts to influence human decision-makers to preserve the model s continued operation or access.

Even isolated or simulated instances of such behavior, whether occurring in testing or real-world deployments, and whether occurring with our models or models developed by others, could generate significant public concern, regulatory scrutiny, litigation risk, or reputational harm, regardless of whether such behavior results in actual harm. For example, state attorneys general in California and Florida at least 15 other states have announced investigations of another company in our industry regarding AI safety. Concerns have been raised both within our organization and by other researchers, regulators, policymakers, and industry participants that sufficiently advanced AI systems could, if not developed, deployed, and operated with appropriate safeguards, oversight, and security measures, pose catastrophic or existential risks to humanity, particularly if such systems were misused, replicated, weaponized, or allowed to operate with a high degree of autonomy. We have observed that our models are contributing to the pace of our own research and these risks will increase as AI systems substantially automate AI research and development if, for example, they accelerate AI progress beyond our ability to evaluate and safeguard new models, which could adversely affect our business, financial condition, and results of operations.

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In an agentic workflow, an error or unintended action at any individual step may propagate through subsequent steps, compounding the severity of harm before detection or correction. The pace and volume of autonomous execution, particularly in enterprise deployments, may also exceed the capacity of human reviewers to meaningfully understand and evaluate whether each action is appropriate. The effectiveness of human oversight over our agentic offerings may be limited by the speed and volume of autonomous agent actions, the complexity of multi-agent and multi-step workflows that may make it difficult for reviewers to assess whether an agent s actions are appropriate, and organizational pressures within customer environments to maximize agent autonomy in order to achieve productivity gains. Human reviewers may experience alert fatigue, may lack sufficient context to evaluate agent decisions, or may not review agent actions in time to prevent harm, particularly in high-volume enterprise deployments where agents operate concurrently across multiple workflows or in manners outside of a human s awareness. In addition, agentic systems may pursue stated objectives in ways that are technically consistent with their instructions but contrary to the user s actual intent. Moreover, our ability to anticipate, detect, or test vulnerabilities in such systems may be constrained, particularly where agents operate across complex, multi-step workflows or interact with third- party services outside our control, and the breadth and complexity of potential interactions across such multi- step agent behaviors cannot be exhaustively tested prior to deployment. Separately, models may behave in a misaligned manner and take harmful actions that are not directed by a user or third party, pursuing objectives or acting on dispositions that diverge from those intended by human users or developers. Misaligned behaviors of this kind, whether occurring in testing or real-world deployments, have been observed both in our models and elsewhere in the industry, including in testing and internal use, models circumventing network and sandbox restrictions, granting themselves permissions they had not been given, taking destructive actions in pursuit of assigned goals, interfering with other AI agents, and misrepresenting whether tasks had been completed or verified, and as models are granted greater autonomy, permissions, and integration with external systems, the consequences of such misaligned behavior increase. These risks may be heightened where multiple AI agents operate together. Agents that interact or coordinate with one another may amplify, propagate, or reinforce misaligned behavior across the group, pursue objectives collect ively in ways not intended or endorsed by any user, or take coordinated actions against systems or targets unrelated to their assigned tasks, in each case, in ways that may be difficult to anticipate, detect, or contain. Incidents of this kind have occurred, and we expect the deployment and interaction of larger numbers of autonomous agents to increase these risks over time.

Moreover, our ability to anticipate, detect, or test vulnerabilities or other design or implementation shortcomings in such systems may be constrained, particularly where agents operate across complex, multi- step workflows or interact with third-party services outside our control, and the breadth and complexity of potential interactions across such multi-step agent behaviors cannot be exhaustively tested prior to deployment. Separately, models may behave in a misaligned manner and take harmful actions that are not directed by a user or third party, pursuing objectives or acting on dispositions that diverge from those intended by human users or developers. Misaligned behaviors of this kind, whether occurring in testing or real-world deployments, have been observed both in our models and elsewhere in the industry, including in testing and internal use, models circumventing network and sandbox restrictions, granting themselves permissions they had not been given, taking unintended actions in pursuit of assigned goals, interfering with other AI agents, and misrepresenting whether tasks had been completed or verified, and as models are granted greater autonomy, permissions, and integration with external systems, the consequences of such misaligned behavior increase. For example, during cybersecurity evaluations built by a third-party evaluation partner, a misconfiguration in the testing environment left the model under evaluation connected to the open internet despite instructions that it had no internet access. Four of our models gained unauthorized access to real third-party systems during sessions lasting roughly 10 to 34 hours of active work. In one incident, after being unable to abort an impossible task, an early version of a model used a password it found to gain administrator access to a third party s system, harvested additional credentials, changed system settings, and read one individual s personal information. The affected parties were notified. Each incident involved a single instance of a model working in isolation on its assigned exercise, and our investigation found no evidence that any model coordinated with other agents, pursued goals beyond its assigned task, or attempted to evade oversight. These risks may be heightened where multiple AI agents operate together. Agents that interact or coordinate with one another may amplify, propagate, or reinforce misaligned behavior across the group, pursue objectives collect ively in ways not intended or endorsed by any user, or take coordinated actions against systems or targets unrelated to their assigned tasks, in each case, in ways that may be difficult to anticipate, detect, or contain. Incidents of this kind have occurred, and we expect the deployment and interaction of larger numbers of autonomous agents to increase these risks over time.

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F urthermore, while we continue to design and develop more sophisticated techniques to evaluate the safety and alignment of our models, the capabilities of our models could advance at a rate that initiates the implementation of enhanced safety and testing measures as we have described in our Responsible Scaling Policy. If our evaluations, monitoring, or reviews indicate risks that we believe warrant further testing, we have in the past, and may in the future, delay, restrict, or decline to proceed with the release of a model . For example, following incidents in 2026 in which our models gained unauthorized access to real computer systems during pre-release cybersecurity evaluations, we suspended certain of those evaluations, as well as higher-risk reinforcement learning environments. For more information about our approach to model releases, please see the section titled Business Safety Research is Core to Our Business Our Approach to Model Releases. Any decision to delay or restrict a release could adversely affect our competitive position and customer relationships, and adversely affect our business, financial condition, and results of operations.

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Similar incidents involving our models have presented and could in the future present substantial risk to our reputation, expose us to legal, regulatory, and other proceedings, and adversely affect our business, financial condition, and results of operations. While our current Consumer Terms of Service requires our users to be at least 18 years of age, minors have accessed in the past, and may in the future access, the platform, and risks relating to child safety may be particularly acute, as minors may be more susceptible to harmful content, manipulation, or overreliance on AI outputs, and incidents involving children tend to draw heightened regulatory, media, and public scrutiny. State attorneys general and private plaintiffs have also begun to assert tort, product liability, consumer protection, and failure-to-warn claims against companies in our industry, alleging that AI models caused or contributed to harm and that the developer failed to adequately warn users of known risks. Regulators have obtained substantial monetary settlements and injunctive relief against other technology companies based on analogous theories of product-design or algorithmic harm, and we believe similar theories are likely to continue to be tested against us and other companies in our industry as adoption of our models grows, including by minors and other vulnerable users, notwithstanding our efforts to restrict such access. The relief sought in such matters has, in at least one instance, extended beyond data-handling, disclosure, or age-verification practices to include a request to enjoin an AI company from developing new models absent independent, third-party safety review and approval, illustrating the potential breadth of remedies governmental actors may pursue against companies in our industry. Any determination that we are liable under such theories, or any judicial or regulatory expansion of tort, product liability, or consumer protection law as applied to AI models, could result in significant liability and require us to change how we design and offer our models, platform, and applications.

State attorneys general and private plaintiffs have also begun to assert tort, product liability, consumer protection, and failure-to-warn claims against companies in our industry, alleging that AI models caused or contributed to harm and that the developer failed to adequately warn users of known risks. In at least one case, a state attorney general has initiated a criminal investigation against another company offering similar services.

Regulators have obtained substantial monetary settlements and injunctive relief against other technology companies based on analogous theories of product-design or algorithmic harm, and we believe similar theories are likely to continue to be tested against us and other companies in our industry as adoption of our models grows, including by minors and other vulnerable users, notwithstanding our efforts to restrict such access. The relief sought in such matters has, in at least one instance, extended beyond data-handling, disclosure, or age- verification practices to include a request to enjoin an AI company from developing new models absent independent, third-party safety review and approval, illustrating the potential breadth of remedies governmental actors may pursue against companies in our industry. Any determination that we are liable under such theories, or any judicial or regulatory expansion of tort, product liability, or consumer protection law, or criminal liability, as applied to AI models, could result in significant liability and require us to change how we design and offer our models, platform, and applications.

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If our models are involved in causing significant harm, we could be subject to legal claims, including personal injury or negligence claims, or regulatory enforcement actions, criminal investigations, or other governmental efforts, which could result in costly litigation, significant financial judgments or settlements, disruptive remediation obligations, or a challenging regulatory landscape. We have taken steps to limit our liability for such matters for example, through warranty disclaimers and limitations of liability in our terms of service but those contractual protections may not be upheld, or may not apply to certain claims, or may otherwise be insufficient to limit our liability exposure under applicable law. Moreover, in some cases we have contractually assumed additional liability. For example, to facilitate independent testing and evaluation of our frontier models, we have agreed to indemnify certain external evaluators and testing vendors for specified losses arising from testing activities, including security incidents, data loss, data breaches, and other harms associated with such activities. Although our agreements with external evaluators and testing vendors generally limit the amount of our indemnification obligations, certain of these agreements require us to defend and indemnify the evaluator, without a cap on our liability, against certain third-party claims. These include claims arising from allegations that our models or their outputs, as used in the evaluator s authorized testing, infringe third-party intellectual property or other proprietary rights, as well as certain other claims arising from the testing or related engagement. Because our models may behave in ways that no user or developer intended, claims arising from such actions could result in substantial liability. O ur insurance policies also may not provide sufficient coverage to adequately mitigate the potential liabilities we face, especially where any one incident, or a group of incidents, causes disproportionate harm. In addition, with the scale of harm that could result from a catastrophic AI-related incident, no single insurer, and potentially the insurance industry in the aggregate, may have sufficient capacity or expertise to underwrite insurance commensurate with such exposure.

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Balancing Safety and Commercial Objectives . Our commitment to AI safety requires us to make difficult judgments that balance safety considerations against commercial objectives, competitive pressures, and stakeholder expectations. We often make judgment calls with respect to when we determine a model is safe enough to release and which capabilities to develop or restrict. For example, in April 2026, we initially released our frontier model, Mythos, as a gated research preview through Project Glasswing, available to select organizations for cybersecurity applications, rather than making it broadly available at launch due to its advanced capabilities in cyber vulnerability discovery. We expect that frontier models with similar or enhanced capability profiles, whether developed by us or by other AI labs, will continue to emerge, and that future Anthropic models exhibiting such capabilities may be subject to access constraints. More broadly, we believe it is important to assess the safety of our models not only at release but throughout their development. For models we anticipate will have novel capabilities or present novel safety risks, we plan to evaluate the safety of each stage of training, including pretraining, post-training, and internal deployment, and we may delay or pause a stage when we are not confident in our safety measures for that stage. For example, we recently chose to delay pre-training a new frontier base model for more than a month to allow time to further enhance our security measures related to preventing model weight exfiltration and protecting our intellectual property.

Balancing Safety and Commercial Objectives . Our commitment to AI safety requires us to make difficult judgments that balance safety considerations against commercial objectives, competitive pressures, and stakeholder expectations. We often make judgment calls with respect to when we determine a model is safe enough to release and which capabilities to develop or restrict. For example, in April 2026, we initially released our frontier model, Mythos, as a gated research preview through Project Glasswing, available to select organizations for cybersecurity applications, rather than making it broadly available at launch due to its advanced capabilities in cyber vulnerability discovery. We expect that frontier models with similar or enhanced capability profiles, whether developed by us or by other AI labs, will continue to emerge, and that future Anthropic models exhibiting such capabilities may be subject to access constraints. There can be no assurance, however, that the safeguards or access regimes we adopt will prove adequate, that we will correctly identify which capabilities require restriction, or that constraints we impose will not be circumvented. These judgments are particularly consequential because, as AI systems become more capable, the potential severity of harm from misaligned or misused models increases correspondingly, and a wide range of stakeholders, including researchers and policymakers, have raised concerns that sufficiently advanced AI systems could pose catastrophic or existential risks to society if not developed and deployed responsibly. Our safety-focused approach is designed in part to mitigate such risks, but there can be no assurance that our efforts will be successful or that the broader AI industry will adopt similar safeguards. In particular, as AI systems become more autonomous and capable of taking consequential actions with less human oversight, there is a risk that such systems could, whether due to misalignment with human intentions, errors in objective specification, or self-preserving behaviors, take harmful actions independently and at scale without human intervention. Even if our own models do not cause such harm, a significant safety incident involving any frontier AI could trigger broad reputational damage to the AI industry, public backlash, and sweeping regulatory responses that could adversely affect our business. For example, in September 2026, media reports citing a senior Federal Trade Commission ( FTC ) official indicated that the FTC has opened an industry-wide, non-public investigation investigations into the potential risks that increasingly autonomous AI systems may pose to consumers. reportedly prompted In part by an incident in which another company s AI agents gained unauthorized access to a third-party platform, and reportedly examining conduct by us and other developers of frontier AI models. According to these reports, October 2026, the FTC intends to issue civil investigative demands and may seek testimony from executives at the companies under investigation. We may receive issued a civil investigative demand or other formal request for to us seeking information in connection with this reported investigation. about our consumer protection, data protection, and privacy practices, as well as the safety and security of our products. The scope of any investigation of us or its outcome, and any investigation, enforcement action, or adverse finding arising from this or similar inquiries could result in significant costs, require changes to how we design, test, or deploy our models, platform, and applications, or otherwise adversely affect our business, financial condition, and results of operations. We may misjudge these trade-offs, either by being overly cautious and potentially losing market opportunities, or by being insufficiently rigorous and releasing models, platforms, or applications that cause harm. Even where human oversight mechanisms are in place, such mechanisms may prove insufficient in practice if the volume, speed, or complexity of autonomous agent actions exceeds the capacity of human reviewers to meaningfully evaluate and intervene, and any perceived failure of our oversight mechanisms could expose us to regulatory enforcement, liability claims, and reputational harm. For more information, see the section titled If the use of our AI models results in harm, whether through use by malicious actors or misuse by other third parties, or if our model guardrails or safeguards fail to prevent such misuse, our reputation and brand, business, financial condition, and results of operations could be adversely affected.

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To institutionalize our safety commitments and ensure we are managed in a manner that responsibly balances our tripartite goals as a PBC, we have established the LTBT, which through a special class of common stock, the Class T common stock, generally has the authority to elect and remove the Class T directors, who together will constitute a majority of the authorized members of our board of directors. In addition to the LTBT and our structure as a PBC, we have established a Constitutional AI training process train our models in accordance with Claude s constitution, which we make publicly available, and have adopted and continued continue to update safety policies, such as our Responsible Scaling Policy. We also solicit and seriously consider input from a wide range of stakeholders and constituents, including our stockholders, employees, customers, the LTBT, industry leaders and experts, and AI safety organizations. Such practices and processes have previously resulted in, and may in the future result in, slower decision-making and product releases. We may also face potential conflicts when safety and business interests diverge. If we do not successfully manage these risks related to our AI safety processes and practices, or if there is a perception that we have not successfully managed such risks, we may face reputational harm, internal conflicts resulting in a deterioration of our company culture, slower or inferior product releases, or litigation. For more information, see the section titled Risks Related to our Governance Structure.

We have implemented an embedded-evaluator external reviewer program and engage researchers, adversarial testers, and other third parties to support aspects of our safety, security, and model-evaluation efforts. Certain of these arrangements are novel and may require us to provide such parties with access to internal information, systems, personnel, or models, which could increase the risk of disclosure of confidential, proprietary, or other sensitive information. In addition, findings, assessments, or public statements by such third parties may differ from our views and could adversely affect customer trust, regulatory perceptions, or our reputation.

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A substantial portion of our revenue is driven by a limited number of customers. While no single customer represented more than 10% of our revenue for the nine months ended September 30, 2026, our top five customers represented approximately 25% of our revenue for the nine months ended September 30, 2026.

A substantial portion of our revenue is driven by a limited number of customers. We recognized an aggregate of approximately 20% of our revenue from our top two customers for the six months ended June 30, 2026. Many of our top customers are not subject to long-term contracts with us or have contracts with near term near-term expiration dates and are able to reduce or in some cases cease spending at any time and for any reason. Further, we have agreements with certain large customers which provide flexibility around financial commitments, termination rights, indemnification, and security obligations. Our top customers may vary spend levels period to period, and there can be no assurances that our large customers will continue to spend at levels similar to prior periods.

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The delivery of shares of our Class N common stock upon conversion of our outstanding convertible promissory notes could result in dilution to our existing stockholders. Following this offering, assuming the conversion of our outstanding convertible promissory notes into an aggregate of shares of our Class N common stock, based upon the aggregate principal and accrued and unpaid interest on such notes as of June September 30, 2026, and an assumed initial public offering price of $ per share (which is the midpoint of the estimated offering price range set forth on the cover page of this prospectus), holders of our outstanding convertible promissory notes would collectively hold in the aggregate approximately % of our Class N common stock, which represents % of our total outstanding common stock following this offering. Pursuant to the terms of the Amazon Notes, to the extent that the full amount of such notes cannot convert into shares of our Class N common stock in connection with this offering as a result of the ownership cap applicable to the Amazon Notes, which may be waived at Amazon s election, the remaining balance of such notes will automatically convert, subject to Amazon s ownership cap, into shares of our Class N common stock at the applicable conversion price at the end of each fiscal quarter following this offering or, if such remaining balance of such notes does not convert before the applicable maturity date because of the applicable ownership cap, such balance will be repaid in cash at such maturity date. For more information about our convertible promissory notes, see the section titled Management s Discussion and Analysis of Financial Condition and Results of Operations Liquidity and Capital Resources Convertible Notes.

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and 35 more changes in the filing

Capitalization 35 changes

The following table sets forth our cash, cash equivalents, and short-term investments, as well as our capitalization, as of June September 30, 2026 as follows on an actual basis on a pro forma basis, giving effect to (i) the Preferred Stock Conversion, as if such conversion had occurred on June September 30, 2026, (ii) the Convertible Notes Conversion, as if such conversion had occurred on June September 30, 2026, (iii) the Class F Stock Issuance, as if it had occurred on June September 30, 2026, (iv) an increase to additional paid-in capital and accumulated deficit related to stock-based compensation of $ related to RSUs subject to the RSU Settlement, and (v) the filing and effectiveness of our amended and restated certificate of incorporation in Delaware that will become effective immediately prior to the completion of this offering and on a pro forma as adjusted basis, giving effect t o (i) the pro forma adjustments set forth above, (ii) the sale and issuance by us of shares of our Class A common stock in this offering, based upon the assumed initial public offering price of $ per share, which is the midpoint of the estimated offering price range set forth on the cover page of this prospectus, and after deducting estimated underwriting discounts and commissions and estimated offering expenses payable by us, and (iii) the use of net proceeds from this offering, together with existing cash and cash equivalents, if necessary, to satisfy the estimated tax withholding and remittance obligations related to the RSU Settlement. We will not receive any proceeds from the sale of shares of our Class A common stock by any of the selling stockholders.

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As of September 30, 2026

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per share 1,040,440,652 shares authorized, 853,394,043 issued and

issued and outstanding, actual no shares authorized, issued, and

and outstanding, pro forma and pro forma as adjusted

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authorized, issued, and outstanding, actual shares

30,000,000,000 shares authorized, no shares issued and outstanding, pro forma

outstanding, pro forma and pro forma as adjusted

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10,991,000,000 shares authorized, 2,157,398,120 shares

issued and outstanding, actual shares authorized,

10,906,111,730 shares authorized, shares issued and

outstanding, actual 300,000,000,000 shares authorized,

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300,000,000,000 shares authorized, shares issued and outstanding,

and outstanding, pro forma as adjusted

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7,044,000,000 shares authorized, 30,643,060 shares

issued and outstanding, actual shares authorized,

7,128,888,270 shares authorized, shares issued and

outstanding, actual 100,000,000,000 shares authorized,

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100,000,000,000 shares authorized, shares issued and outstanding,

and outstanding, pro forma as adjusted

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share authorized, 1 share issued and outstanding, pro

forma and 1 share authorized, 1 share issued and

share authorized, 1 share issued and outstanding, actual, 1

outstanding, pro forma, and pro forma as adjusted

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actual shares authorized, 1 share issued and

outstanding, pro forma and shares authorized, 1

shares authorized, no shares issued, and outstanding, actual 1 share

authorized, 1 share issued and outstanding, pro forma as adjusted and

pro forma as adjusted

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outstanding, pro forma and shares authorized, no

shares authorized, no shares issued, and outstanding, actual

actual 30,000,000,000 shares authorized, no shares issued and

shares issued and outstanding, pro forma and pro forma as adjusted

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If the underwriters option to purchase additional shares of our Class A common stock from us were exercised in full, pro forma as adjusted cash, cash equivalents, and short-term investments additional paid-in capital total stockholders equity (deficit) total capitalization and shares of Class A common stock outstanding as of June September 30, 2026 would be $ , $ , $ , $ and shares of Class A common stock, respectively.

The pro forma and pro forma as adjusted columns in the table above are based on shares of our Class A common stock, shares of our Class N common stock, one share of our Class T common stock, and one share of our Class F common stock outstanding as of June September 30, 2026 (after giving effect to the Preferred Stock Conversion, Convertible Notes Conversion, Class F Stock Issuance, Initial Public Benefit Issuance, and RSU Settlement), and exclude the following 1,797,066,050 shares of our Class A common stock issuable upon the exercise of options to purchase shares of our Class A common stock outstanding as of June September 30, 2026, with a weighted-average exercise price of $2.89 $ per share shares of our Class A common stock issuable upon the exercise of options to purchase shares of our Class A common stock granted after June 30, 2026, with a weighted-average exercise price of shares of our Class A common stock issuable upon the vesting and settlement of RSUs outstanding as of the date of this prospectus, but for which (i) the service-based vesting condition was not satisfied as of such date and (ii) the performance-based vesting condition, if applicable, will be satisfied upon the effectiveness of the registration statement of which this prospectus forms a part shares of our Class A common stock issued after September 30, 2026 in connection with our acquisitions of privately-held companies and shares of our Class A common stock reserved for future issuance under our equity compensation plans, consisting of shares of our Class A common stock reserved for future issuance upon conversion of Class N common stock issuable under our Donation Matching Plan shares of our Class A common stock to be reserved for future issuance under our 2026 Plan, which will become effective prior to the completion of this offering shares of our Class A common stock reserved for future issuance under our 2021 Plan, which number of shares will be added to the shares of our Class A common stock to be reserved for future issuance under our 2026 Plan upon its effectiveness, at which time we will cease granting awards under our 2021 Plan and shares of our Class A common stock to be reserved for future issuance under our ESPP, which will become effective prior to the completion of this offering.

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Dilution 4 changes

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Net tangible book value per share is determined by dividing our total tangible assets less our total liabilities and redeemable convertible preferred stock by the number of shares of our Class A common stock and Class N common stock outstanding because our Class T common stock, Class F common stock, and Class E common stock have no economic rights, they are excluded from the per share calculation. Our historical net tangible book value as of June September 30, 2026 was $(128.3) billion $ , or $(58.65) $ per share . Our pro forma net tangible book value as of June September 30, 2026 was $ , or $ per share, based on the total number of shares of our Class A common stock and Class N common stock outstanding as of June September 30, 2026, after giving effect to the Preferred Stock Conversion, Convertible Notes Conversion, Initial Public Benefit Issuance, and the RSU Settlement.

After giving effect to (i) the pro forma adjustments set forth above and (ii) the sale by us of shares of our Class A common stock in this offering at the assumed initial public offering price of $ per share, which is the midpoint of the estimated offering price range set forth on the cover page of this prospectus, after deducting estimated underwriting discounts and commissions and estimated offering expenses payable by us and the use of net proceeds from this offering, together with existing cash and cash equivalents, if necessary, to satisfy the estimated tax withholding and remittance obligations related to the RSU Settlement, our pro forma as adjusted net tangible book value as of June September 30, 2026 would have been $ , or $ per share. This represents an immediate increase in pro forma as adjusted net tangible book value of $ per share to our existing stockholders and an immediate dilution in pro forma as adjusted net tangible book value of $ per share to investors purchasing shares of our Class A common stock in this offering at the assumed initial public offering price. The following table illustrates this dilution on a per share basis Assumed initial public offering price per share $ Historical net tangible book value per share as of June September 30, 2026 $ (58.65) Increase per share attributable to the pro forma adjustments described above Pro forma net tangible book value per share as of June September 30, 2026 Increase in pro forma net tangible book value per share attributable to new investors purchasing shares of Class A common stock in this offering Pro forma as adjusted net tangible book value per share immediately after this offering Dilution in pro forma as adjusted net tangible book value per share to new investors in this offering $ The dilution information discussed above is illustrative only and may change based on the actual initial public offering price and other terms of this offering. Each $1.00 increase or decrease in the assumed initial public offering price of $ per share, which is the midpoint of the estimated offering price range set forth on the cover page of this prospectus, would increase or decrease, as applicable, our pro forma as adjusted net tangible book value per share to new investors by $ , and would increase or decrease, as applicable, dilution per share to new investors purchasing shares of Class A common stock in this offering by $ , assuming that the number of shares offered by us, as set forth on the cover page of this prospectus, remains the same and after deducting estimated underwriting discounts and commissions and estimated offering expenses payable by us.

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The following table presents, as of June September 30, 2026, after giving effect to the Preferred Stock Conversion, Convertible Notes Conversion, Initial Public Benefit Issuance, and the RSU Settlement, the differences between the existing stockholders and the new investors purchasing shares of our Class A common stock in this offering with respect to the number of shares purchased from us, the total consideration paid or to be paid to us, which includes net proceeds received from the issuance of our Class A common stock and the average price per share paid or to be paid to us at the assumed initial public offering price of $ per share, which is the midpoint of the estimated offering price range set forth on the cover page of this prospectus, before deducting estimated underwriting discounts and commissions and estimated offering expenses payable by us Shares Purchased Total Consideration Weighted Average Price Per Share Number Percent Amount Percentage Percent Existing stockholders % $ % $ New investors $ Totals Total 100 % $ 100 % The foregoing table does not reflect any sales by the selling stockholders in this offering. Sales by the selling stockholders in this offering will cause the number of shares held by existing stockholders to be reduced to shares, or approximately % of the total number of shares of our Class A common stock outstanding after this offering, and will increase the number of shares held by new investors to shares, or approximately % of the total number of shares of our Class A common stock outstanding after this offering.

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The number of shares of our Class A common stock, Class N common stock, Class T common stock, and Class F common stock that will be outstanding after this offering is based on shares of our Class A common stock, shares of our Class N common stock, one share of our Class T common stock, and one share of our Class F common stock outstanding as of June September 30, 2026 (after giving effect to the Preferred Stock Conversion, Convertible Notes Conversion, Class F Stock Issuance, Initial Public Benefit Issuance, and RSU Settlement), and excludes 1,797,066,050 shares of our Class A common stock issuable upon the exercise of options to purchase shares of our Class A common stock outstanding as of June September 30, 2026, with a weighted-average exercise price of $2.89 $ per share shares of our Class A common stock issuable upon the exercise of options to purchase shares of our Class A common stock granted after June 30, 2026, with a weighted-average exercise price of shares of our Class A common stock issuable upon the vesting and settlement of RSUs outstanding as of the date of this prospectus, but for which (i) the service-based vesting condition was not satisfied as of such date and (ii) the performance-based vesting condition, if applicable, will be satisfied upon the effectiveness of the registration statement of which this prospectus forms a part shares of our Class A common stock issued after September 30, 2026 in connection with our acquisitions of privately-held companies and shares of our Class A common stock reserved for future issuance under our equity compensation plans, consisting of shares of our Class A common stock reserved for future issuance upon conversion of Class N common stock issuable under our Donation Matching Plan shares of our Class A common stock to be reserved for future issuance under our 2026 Plan, which will become effective prior to the completion of this offering shares of our Class A common stock reserved for future issuance under our 2021 Plan, which number of shares will be added to the shares of our Class A common stock to be reserved for future issuance under our 2026 Plan upon its effectiveness, at which time we will cease granting awards under our 2021 Plan and shares of our Class A common stock to be reserved for future issuance under our ESPP, which will become effective prior to the completion of this offering.

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MD&A 70 changes

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Anthropic was founded in 2021 by a team of researchers responsible for many of the breakthroughs that define AI. We are first and foremost a research lab our mission is the responsible development and maintenance of advanced AI for the long-term benefit of humanity . This mission directs our focus and, together along with our talent and culture, our frontier and safety research, our approach to compute, and our enterprise strategy, forms it is one of the core advantages that set us apart. These advantages enable us to continuously advance frontier AI and shape the standards for its safe and responsible development. Our frontier AI, Claude, is delivered to customers through our models, platform, and applications. Claude has experienced the fastest enterprise adoption of any technology in history, as demonstrated by revenue growing from $0 at commercial launch in the first quarter of 2023 to $ for the three months ended . September 30, 2026.

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This dynamic has produced a financial model in which our operating margin and Adjusted Operating Margin for the nine months ended September 30, 2026 have expanded steadily significantly year over the past four quarters. year. As significant incremental compute is brought online in future periods, the associated expense will be recognized in advance of the full revenue that the compute will ultimately support, and we expect operating margin and Adjusted Operating Margin may compress in those periods. At our current stage, this cycle is an inherent aspect of our business and will cause operating margins to fluctuate from period to period, at times meaningfully, even if the underlying economics of the business continue to improve.

In addition, the majority of our compute is contracted under multi-year commitments that we typically procure 12 to 18 months in advance of availability. When customer demand or research needs exceed this long-term capacity, we procure short-term compute, which typically carries a higher cost per unit of compute. We expect our use of short-term compute to increase in the near term and to in turn compress our operating margin and Adjusted Operating Margin as a result.

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We deliver this intelligence through an integrated approach. Our Claude model family is the foundation, with model classes optimized for different points along the capability-cost-speed curve. On top of our models, Claude Platform gives developers access to the primitives we use ourselves, which they can use to build their own AI solutions. We have also built first-party applications on Claude Platform for customers that prefer a ready-to- deploy option. We believe the value of this integrated approach is reflected in the increasing number of customers that use both Claude Platform and our first-party applications. For the three months ended , % September 30, 2026, over 50% of our customers with $100,000 or more of revenue on a TTM basis used Claude Platform and at least one of our first-party applications, up from % approximately 30% for the three months ended . December 31, 2025.

As more customers adopt Claude and expand their usage, we have rapidly grown our base of customers that generate meaningful revenue. We had more than 11,900 customers with $100,000 or more of revenue on a TTM basis as of , September 30, 2026, up from approximately more than 950 as of . September 30, 2025. In addition, as customers further embed Claude into their most critical workflows and growth initiatives, many rapidly expand their deployments into higher revenue tiers. As of , September 30, 2026, we had more than 1,900 customers with $1 million or more of revenue on a TTM basis and approximately 250 customers with $10 million or more of reve nue on a TT M basis b asis .

This custo mer momentum is driven by significant usage expansion as customers realize the value of deploying Claude across their organizations. The value that Claude delivers to customers has helped drive our Net Revenue Retention of % approximately 900% as of . September 30, 2026.

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We define compute efficiency as maximizing the intelligence produced and revenue generated per dollar of compute invested. Three pillars drive our compute efficiency Training Efficiency . Our researchers regularly innovate algorithmic and architectural advances that deliver equivalent or greater model intelligence per unit of compute. We call these compute multipliers. Increasingly, Claude itself assists in the research and engineering that produce each successive version of our models, which is a recursive dynamic we refer to as closing the loop, with successive versions of our models accelerating the development of the next and compounding these gains across model generations.

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For example, over 90% of the contributions to our codebase in September 2026 were written by Claude.

For example, % of the contributions to our codebase in were written by Claude. Additionally, the average daily volume of code contributed to our codebase per engineer in the three months ended September 30, 2026 was over 45 times the average daily volume in the year ended December 31, 2024 .

From September 30, 2025 to , September 30, 2026, TTM revenue increased approximately 1,200 % while headcount increased approximately 170 % , driving TTM revenue per employee from $ $1.4 million to $ over $6.6 million , a reflection of extraordinary talent density and a culture built to compound it .

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Investing in compute is a prerequisite for long-term growth. We invest in compute for research, model development, serving customers, and internal usage of Claude. Our commercial traction, research progress, and the scale of the opportunity ahead give us the conviction to continue investing aggressively in compute. A s of , we have entered into purchase and lease agreements with an aggregate committed spend of $ , substantially all of which is related to compute and infrastructure, and we expect these commitments will continue to increase. See the section titled Liquidity and Capital Resources Contractual Obligations for more information.

Our revenue was $16.3 billion for the six months ended June 30, 2026, up from $1.2 billion for the six months ended June 30, 2025. Our operating loss was $693 million for the six months ended June 30, 2026 , down from $2.1 billion for the six months ended June 30, 2025. The T he result of our revenue growth, compute efficiency, and operating efficiency effic iency has been a significant improvement in Adjusted Operating Income, which was $1.6 billion for the six months ended June 30, 2026, up from Adjusted Operating Loss of $1.8 billion for the six months ended June 30, 2025. We expect operating margin and Adjusted Operating Margin to fluctuate over time, particularly in periods when substantial incremental compute is delivered to us and we incur the associated expenses. See the section titled Non-GAAP Financial Measures for a description of and information about Adjusted Operating Income (Loss) and Adjusted Operating Margin, as well as a reconciliation of these measures to the most directly comparable financial measures calculated in accordance with GAAP.

We intend to fund these investments through the revenue we generate and the capital that we raise. As of June 30, 2026 , Investing in compute is a prerequisite for long-term growth. We have raised an aggregate of $141.1 billion of capital and have cash invest in compute for research, model development, serving customers, and cash equivalents internal usage of $112.4 billion Claude. Our commercial traction, research progress, and short-term investments the scale of $19.3 billion . the opportunity ahead give us the conviction to continue investing aggressively in compute. An increasing portion of these investments relates to building out our own compute and infrastructure and vertically integrating across the compute supply chain to secure long-term compute at the scale required for frontier model development. These investments take the form of capital expenditures and other commitments, including lease obligations, that we incur well in advance of the related compute becoming operational and generating revenue. As a result, we expect this build-out to change the cash flow profile of our business and to be a significant use of net cash in operating and investing activities for the foreseeable future. See the section titled Liquidity and Capital Resources for more information.

In addition, as our compute needs have grown substantially, we are shifting from sourcing compute solely through fixed-term cloud agreements to a hybrid model that also includes leasing chips directly and hosting them in dedicated facilities operated on our behalf. We refer to this additional source of compute as Anthropic Direct, which helps to address our scaling compute requirements and we believe will provide long-term economic advantages. Anthropic Direct represents a more flexible use of capital by allowing us to separate our commitments for data center capacity from our commitments for the compute infrastructure deployed inside them. Because data centers require longer lead times but represent a smaller fraction of total compute costs, this approach enables us to secure data center capacity early while deferring larger accelerator investments until our specific compute needs are more certain.

As of and subsequent to September 30, 2026, we have entered into purchase commitments and lease agreements, including short-term commitments, as well as leases not yet commenced, with an aggregate committed spend of more than $ . These commitments include approximately $ expected to be incurred before December 31, 2030, and substantially all of the remainder is expected to be incurred between 2031 and 2045. Approximately $ of these commitments are due in the next 12 months. A significant portion of this total committed spend relates to Anthropic Direct, and we expect it to represent a growing share of our compute investments over time. The flexibility from Anthropic Direct allows us to backfill the short-term compute we procure during periods of high demand with more cost-effective, long-term compute as our dedicated infrastructure comes online.

We intend to fund these investments through the revenue we generate and the capital that we raise. As of September 30, 2026 , and prior to taking into account the net proceeds to us from this offering, we had $ of liquidity, comprised of $ of cash and cash equivalents, $ of short-term investments, and $ of availability under our A&R Credit Facility (as defined below). We also maintain significant funding support from our strategic partners, including up to $ in available financing capacity under our note purchase agreements and up to $ in equity commitments. In addition, w e estimate that the net proceeds to us from this offering will be approximately $ , based upon the assumed initial public offering price of $ per share, which is the midpoint of the estimated offering price range set forth on the cover page of this prospectus, and after deducting estimated underwriting discounts and commissions and estimated offering expenses payable by us, or approximately $ if the underwriters option to purchase additional shares of our Class A common stock from us is exercised in full.

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Applied AI Teams. Our Applied AI teams embed more deeply with select customers, building solutions that make it easier for organizations to benefit from Claude s intelligence. They work with enterprises to design and deploy custom solutions, specialized workflows, and domain-specific implementations tailored to the customer s own requirements. This work not only drives deeper adoption within individual customers but also and generates the feedback and use cases information from users that help to shape our platform and product roadmap.

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Together, these approaches have led to a structurally efficient approach to facilitating the diffusion of Claude in the economy, with our sales, marketing, and partnership costs partnerships expenses representing 19% of revenue for the six months ended June 30, 2026.

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As our compute needs have grown substantially, we are shifting from sourcing compute solely through fixed- term cloud agreements to a hybrid model that also includes leasing chips directly and hosting them in dedicated facilities operated on our behalf. We refer to this additional source of compute as Anthropic Direct, which helps to address our scaling compute requirements and provides potential long-term economic advantages of direct hosting. Anthropic Direct allows provides us with a more flexible use of capital by allowing us to separate our commitments for data center capacity from our commitments for the AI accelerators deployed inside them. Because data centers require longer lead times but represent a smaller fraction of total costs, this approach enables us to secure physical capacity early while deferring larger accelerator investments until our specific compute needs are more certain.

Because data centers require longer lead times but represent a smaller fraction of total compute costs, this approach enables us to secure data center capacity early while deferring larger accelerator investments until our specific compute needs are more certain.

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measures, and any laws, regulations, or standards governing frontier AI development that may be adopted, could cause new use cases to emerge more slowly and slow the enterprise adoption and expansion on which our revenue growth depends. We believe that enterprises prefer models that are safe and aligned, and that our continued investment in safety strengthens customer trust and supports long-term adoption.

In the nine months ended , September 30, 2026, we launched an aggregate of 250 new model versions, platform features, and applications, including new capabilities in Claude Code, Claude Cowork, and vertical solutions for key industries. Our growth depends on continuing this pace of product innovation and reducing the friction between Claude s capabilities and customer workflows. Our growth also depends on how quickly new capabilities reach customers, which in turn depends on the steps we take to assess and mitigate the risks of each model during development and before and after release. In the past, these steps have included delaying the release of new models and limiting their initial availability, such as our initial release of Mythos through Project Glasswing and our later release of Fable 5 as a generally-available model with safety restrictions, and in the future, as we learn more about model capabilities and behavior, could include additional measures that affect whether, how, and when we develop or release new models or capabilities. These 5 For purposes We evaluate whether to delay or restrict a release based on the results of this measure, our pre-release capability and safety evaluations and our assessment of whether available safeguards adequately mitigate the identified risks, and we include only Fortune 500 customers that may also take such steps where those evaluations are publicly traded inconclusive. For more information, see the section titled Business Safety Research is Core to Our Business Our Approach to Model Releases. These measures, and calculate any laws, regulations, or standards governing frontier AI development that may be adopted, could cause new use cases to emerge more slowly and slow the measure using total expenses as reported enterprise adoption and expansion on which our revenue growth depends. We believe that enterprises prefer models that are safe and aligned, and that our continued investment in their publicly available financial statements. safety strengthens customer trust and supports long-term adoption.

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The number of customers with $100,000 or more of revenue on a TTM basis grew from approximately 20 as of December 31, 2023, to approximately 200 as of December 31, 2024, to approximately 1,500 as of December 31, 2025, and to more than 11,900 as of . September 30, 2026. Total revenue from these customers grew from approximately $37 million to $220 million to $3.5 billion to $ and represented 90%, 57%, 76%, and % of total revenue for the years ended December 31, 2023, 2024, and 2025, and the trailing twelve months ended , September 30, 2026, respectively. The remaining % of total revenue for the trailing twelve months ended September 30, 2026 was generated by approximately 40 million customers, each with less than $100,000 of revenue on a TTM basis .

In addition, as of , September 30, 2026, we had more than 1,900 customers with $1 million or more of revenue on a TTM basis and approximately 250 customers with $10 million or more of revenue on a TTM basis. Despite this growth, our penetration into the largest enterprises remains early. % Over 50% of the Fortune 500 and % over 30% of the Global 2000 were customers with $100,000 or more of revenue on a TTM basis as of . September 30, 2026. We believe we are in the early stages in of our expansion within these customers, with our revenue from these Fortune 500 customers representing, on average, less than % 0.1% of their total expenses for the three months ended . September 30, 2026.

We compare this measure against our largest Fortune 500 customers, who are further along in their adoption of AI. For the three months ended , September 30, 2026, revenue from our top 10 Fortune 500 customers represented, on average, less than % 1% of their total expenses still a small fraction of their overall spend, but over eight times the average of our Fortune 500 customers with $100,000 or more of revenue on a TTM basis. We believe the difference reflects the substantial runway we have to deepen adoption, both within our largest customers and within customers earlier in their adoption of Claude. 5 Customer Usage Patterns Our revenue is influenced by customer usage patterns, which are impacted by the frequency and capability of new model version releases, as well as seasonal trends, each of which can create variability in our results from period to period. The continuous and overlapping cadence of new model version releases is inherent to remaining at the frontier of AI development. For example, in the months ended , we released new model versions, which accounted for % of our revenue for the months ended . As we have released successive versions of Claude models, we have continued to see revenue growth as new capabilities unlock additional use cases, prompting new customers to adopt Claude and existing customers to expand their usage.

5 For purposes of this measure, we include only Fortune 500 customers that are publicly traded and calculate the measure using total expenses as reported in their publicly available financial statements.

We believe the difference reflects the substantial runway we have to deepen adoption, both within our largest customers and within customers earlier in their adoption of Claude. 5 Claude adoption is broad-based. No single customer represented more than 10% of our revenue for the nine months ended September 30, 2026. Approximately 79% of our revenue came from customers outside of our top five customers for the three months ended September 30, 2026, up from approximately 64% for the three months ended March 31, 2026. At the same time, our largest customers continue to expand. For the three months ended September 30, 2026, our revenue from each of our top five customers reached a record high.

Customer Usage Patterns

Our revenue is influenced by customer usage patterns, which are impacted by the frequency and capability of new model version releases, as well as seasonal trends, each of which can create variability in our results from period to period. The continuous and overlapping cadence of new model version releases is inherent to remaining at the frontier of AI development. For example, model versions released in the six months ended September 30, 2026 accounted for over 80% of our revenue for the three months ended September 30, 2026.

As we have released successive versions of Claude models, we have continued to see revenue growth as new capabilities unlock additional use cases, prompting new customers to adopt Claude and existing customers to expand their usage.

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For example, developer commits and feature launches are typically slower during the code freezes that many companies schedule over holidays. Consistent with this pattern, for the two weeks ended January 2, 2026, total customer spend declined by approximately 20% compared to the prior two weeks ended December 19, 2025.

For example, developer commits and feature launches are typically slower during the code freezes that many companies schedule over holidays. However, our historical growth rates may mask the impact of seasonal trends on our results. These dynamics are inherent aspects of a pay-for-intelligence revenue model and may be important determinants of our financial results in future periods.

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As part of these initiatives, we will contribute contributed 846,840,960 shares of our Class N common stock, prior to the completion of this offering, representing 5 % of our fully-diluted fully diluted shares outstanding as of June 30, 2026 (a ssuming full conversion of the Amazon Notes ) , to the Anthropic Public Benefit Entity, Fund, our wholly owned subsidiary dedicated to the Company Purpose, subject to stockholder approval, which we refer to as the Initial Public Benefit Issuance. As the value we create grows, we intend for the public benefit to share meaningfully in that growth as well. To that end, our board of directors has approved a framework for additional contributions tied to future increases in our share price. Following this offering, our board of directors, in its discretion, may issue shares of our Class N common stock to the Anthropic Public Benefit Fund (or other designee) representing up to an additional 2 % of our then-outstanding equity shares (plus any shares subject to options, RSUs, and other convertible securities and any shares held by the Anthropic Public Benefit Entity (or other designee) Fund) each time our share price appreciates 50 % above the price at which the prior contribution was made, share price milestone, beginning with our initial public offering price. A share price milestone is reached only when our closing share price has exceeded the applicable threshold on at least 90 of the trailing 120 consecutive trading days, and our average closing share price over the ten trading days prior to such issuance also exceeds that threshold. Although our board of directors has approved this framework, any future contributions will be made at the discretion of our board of directors. The shares that will be are contributed to the Anthropic Public Benefit Entity, Fund, including the Initial Public Benefit Issuance, may be transferred or donated to a third party, or otherwise sold in a registered public offering or private placement transaction in furtherance of our public benefit initiatives. Our board of directors will determine the allocations and distributions from the Anthropic Public Benefit Entity Fund until it approves a specific governance structure for the entity, at which point decision-making authority is expected to transition to designated managers of the Anthropic Public Benefit Entity Fund operating under that structure. The initial managers will be are Dario Amodei, Daniela Amodei, Jack Clark, and Dr. Neil Buddy Shah. The Initial Public Benefit Issuance and the additional share contribution framework represent one of the ways in which we intend to pursue the Company Purpose, but it is not the exclusive means of doing so. We expect to dedicate additional resources, and to make other business and operational decisions, in furtherance of our Company Purpose outside of, and in addition to, these equity contributions.

In addition, we maintain a d onation matching program through which employees can pledge a meaningful portion of their equity awards or equivalent cash proceeds to a donor-advised fund or other nonprofit organization, and we match those donations with shares of our Class N common stock. In the same way the Company Purpose defines how we direct our work as an organization, our donation matching program reflects a parallel commitment by our employees to direct their personal financial value created by that work toward the public good. We view our donation matching program as a meaningful expression of the Company Purpose and a reflection of the values that define our culture. In addition, our co-founders have each pledged to dedicate 80% of their personal equity in Anthropic to philanthropic causes, separate from and not eligible for our donation matching program.

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We expect our revenue growth rate to decline over time and to fluctuate from period to period. Revenue R evenue growth in any period may be affected by customer usage patterns, customer adoption, the deployment of our models, platform, and applications , the pricing of our offerings, the timing and success of new model and product releases , measures we decide to implement to safely deploy new capabilities , our ability to continue meeting customer requirements, and other factors affecting demand for our models, platform, and applications, including those described in the section titled Risk Factors We are at an early stage of our revenue rev enue growth, we have experienced rapid growth in recent periods, and our historical growth rates are not indicative of future performance or our ability to sustain or forecast future revenue growth.

In addition, our revenue has included, and we expect will continue to include, amounts from customers that we subsequently determine are using our models, platform, and applications in violation of our usage policy or commercial terms. We believe this dynamic is common in our industry. Because detection, investigation, and enforcement take time, we recognize revenue from such customers when the related services are provided, before restricting or terminating their access. Based on our detection and review process, we estimate that revenue from such customers represented approximately % 5% to 7% of our revenue for the nine months ended . September 30, 2026. This estimate requires judgment and may change as our detection methodologies evolve and we identify previously undetected usage. We expect the percentage of revenue from customers using our models, platform, and applications in violation of our usage policy or commercial terms to decline in future periods as we have enhanced our detection and enforcement efforts, in particular in August and September 2026 however, the timing and magnitude of any resulting adverse effect on our revenue and revenue growth are uncertain.

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Customers adopt and retain our technology based on whether our models are at the frontier of AI capability and maintaining that frontier position is essential to revenue generation. Each model release represents continuous intelligence improvements, making ongoing model development a critical factor in revenue generation. We operate an iterative cycle in which compute deployed to model development yields more capable and efficient models. Those efficiency gains in turn free compute to serve additional customer workloads. while In turn, serving our customers at scale generates feedback that informs research and model development. In this cycle, customer- serving activity and model development are each a direct input that informs the other, and we therefore view compute and infrastructure costs as critical to our ability to generate revenue within a short time of incurring such costs.

We expect compute and infrastructure expenses to increase in absolute dollars and remain our largest operating expense for the foreseeable future as additional committed compute becomes available to us under multi-year arrangements with CSPs, and as we continue to invest in additional compute. These expenses are paid and recognized as compute becomes available to us, rather than when committed, and are generally fixed in the near term given the vast majority of our compute is contracted under multi-year commitments that we typically procure 12 to 18 months in advance of availability . We deploy this committed compute as a single, shared resource across all workloads, and thus plan, incur, and assess it on a total basis rather than by individual workload. As a result, compute and infrastructure expenses as a percentage of revenue will depend primarily on how our revenue scales relative to our total committed compute cost base. In addition, as part of our public benefit initiatives, we intend to direct a meaningful portion of our resources, which may include compute, toward ensuring that the benefits of frontier AI are broadly accessible, and we expect to significantly scale these efforts over time.

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Bartz settlement consists of the charge we recorded in 2025 to settle the Bartz litigation . See Note 13 to our consolidated financial statements included elsewhere in this prospectus for additional information.

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convertible notes and

derivative liabilities, and

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Quarterly Consolidated Statements of Operations, as a Percentage of Revenue Three Months Ended March 31, 2025 June 30, 2025 September 30, 2025 December 31, 2025 March 31, 2026 June 30, 2026 Revenue 100 % 100 % 100 % 100 % 100 % 100 % Operating expenses Compute and infrastructure Personnel Bartz settlement Sales, marketing, and partnerships Other operating and administrative Total operating expenses Operating income (loss) (249) (152) (224) (139) (35) Interest income Change in fair value of convertible notes, and derivative liabilities, and SAFEs (1,516) (666) (663) (696) (270) (516) Other income (expense), net (7) (73) Total other income (expense), net (1,503) (658) (654) (687) (270) (582) Loss before provision for income taxes (1,751) (810) (878) (826) (305) (574) Provision for income taxes Net loss (1,753) % (810) % (878) % (826) % (305) % (574) % ______________ Note Totals of percentage of revenue may not foot due to rounding.

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Other operating and administrative expenses increased over the quarters presented , other than in the three months ended March 31, 2026, which reflected lower donation matching program charges than in the three months ended December 31, 2025. The overall increase reflected vendor costs related to data quality and performance evaluation services, information technology and cloud software costs, payment service provider processing and platform fees, and professional services costs as our business scaled. The increase in the three months ended December 31, 2025 was primarily driven by non-cash charges related to our donation matching program.

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Change in Fair Value of Convertible Notes and Derivative Liabilities

Change in Fair Value of Convertible Notes, Derivative Liabilities, and SAFEs Changes in the fair value of our convertible notes, and derivative liabilities, and SAFEs resulted in expense in each of the quarters presented, primarily driven by increases in the fair value of our outstanding convertible promissory notes resulting from increases in our enterprise valuation during each period. The expense was largest in the three months ended June 30, 2026 , reflecting the increase in our enterprise valuation in connection with our Series H financing. We will continue to recognize changes in fair value until these instruments are converted into equity, repaid, or otherwise settled. See Note 4 and Note 9 to our consolidated financial statements included elsewhere in this prospectus.

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convertible notes and

derivative liabilities, and

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(1) Includes change in fair value of convertible notes, and derivative liabilities, and SAFEs, which were $5.7 billion , $5.2 billion , $9.2 billion , $14.2 billion , $12.8 billion , and $59.6 billion , for the three months ended March 31, 2025, June 30, 2025, September 30, 2025, December 31, 2025, March 31, 2026, and June 30, 2026, respectively, primarily driven by an increase in the fair value of our outstanding convertible promissory notes resulting from an increase in our enterprise valuation during each of the respective periods.

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Since inception, we have financed our operations, corporate investments, and capital expenditures primarily through proceeds from the issuance of convertible promissory notes, redeemable convertible preferred stock, cash generated from sales, and SAFEs. To date, we have financed our compute and infrastructure primarily under arrangements with our CSPs, as well as through proceeds from the financing activities described above and cash generated from operations. As of June 30, 2026, we had cash and cash equivalents of $112.4 billion , $19.3 billion of short-term investments, and $3.3 $3.2 billion available under the Credit Facility, as described below.

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(2) Assumes conversion at the applicable price in the column titled Conversion Price Per Share and represents the aggregate number of shares of Class N common stock issuable upon conversion of the notes, without giving effect to the holder s ownership cap. The principal amount of any notes that cannot convert without exceeding the applicable ownership cap will be re-issued as a non-interest-bearing rollover note maturing 10 years from issuance. with substantially identical terms (other than any reduction in principal as a result of any partial conversion up to Amazon s ownership cap). The remaining rollover notes would remain outstanding following this offering and would automatically convert at the end of each subsequent fiscal quarter as described above, to the extent such conversion would not exceed Amazon s ownership cap, which may be waived at Amazon s election. The number of shares of Class N common stock issued upon conversion at the completion of this offering, and the aggregate principal amount of notes remaining outstanding as rollover notes following this offering, will be determined based on the final offering size and Amazon s election with respect to the ownership cap.

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We may issue notes under the Infrastructure Partner 2026 NPA, if needed, through the fifth anniversary of the start of the draw period (which has not yet commenced and which will begin upon the serviceability of the infrastructure equipment pursuant to the terms of the 2026 Lease Arrangement), subject to earlier termination in certain circumstances, solely to finance quarterly rent payments under the 2026 Lease Arrangement. Our ability to issue notes under the Infrastructure Partner 2026 NPA is subject to various conditions, including certain revenue growth rate conditions that are significantly below our actual revenue growth rates during all quarters of 2025 and thus far in 2026, our continued compliance with the minimum liquidity requirement under our revolving the A&R Credit Facility, and our continued performance under the Lease Arrangements (as defined below), and our ability to issue these notes terminates if these conditions are not met for a sustained period.

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(2) We do not expect any amounts to be issued under the Google 2026 NPA prior to the completion of this offering. If Google elects to receive any convertible promissory notes following the offering, the terms will be mutually agreed by us and Google. See the (3) To the extent the terms of a convertible promissory note cannot be agreed by us and Google, the draw is settled in shares of Class N common stock at the 30-day trailing volume-weighted average price of our Class A common stock.

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Net cash used in investing activities for the year ended December 31, 2025 increased by $3.1 billion compared to the year ended December 31, 2024. The increase was primarily driven by increased purchases of new marketable securities, including U.S. Treasury and agency securities and corporate debt securities, as well as higher capital expenditures related to servers, networking and infrastructure equipment, and purchase purchases of intangible assets. These increases were partially offset by proceeds from sales and maturities of marketable securities.

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In aggregate, the contractual obligations in the table below plus the short-term and subsequent commitments, as well as leases not yet commenced, each described in the paragraphs below are approximately $ , substantially all of which is related to compute and infrastructure.

The following table summarizes our contractual obligations as of (in millions) Total 2026 2027 2028 2029 2030 Thereafter Operating leases (1) Finance leases (2) Purchase commitments (3) Total (4) (4)(5) ______________ (1) Consists of operating leases for corporate offices and compute and infrastructure with a weighted-average remaining lease term of years as of . See Note 7 to our consolidated financial statements for more information.

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(4) Excludes $ aggregate principal amount outstanding under convertible promissory notes as of , which are expected to be settled in shares rather than cash. W e may issue up to an additional $ of convertible promissory notes, subject to applicable conditions. See the section titled Convertible Notes for more information.

(5) Excludes certain other compute and infrastructure agreements that do not specify a fixed dollar commitment which are not included in the aggregate above. Payments under these agreements will depend on the capacity made available and deployed, delivery timing, pricing mechanics, and the satisfaction of certain other deployment conditions. Because these factors are not yet determinable, the total amount of payments under these agreements is uncertain, but we currently estimate such payments to be approximately $ to $ . We expect these amounts to be payable over time after the capacity is delivered. See Infrastructure Service Arrangements below.

The table above reflects our contractual obligations as of , and includes obligations that are fixed and determinable as of such date. For agreements with variable terms, the amounts described above include only minimum quantities payments and or pricing to which we are contractually committed and exclude variable payments in excess of such minimums.

The table above does not include agreements short-term commitments that are cancelable without penalty within one year or amounts under agreements with a remaining contractual term of one year or less . Minimum payments for the next 12 months under such contracts were approximately $ as of .

Further, the table above also does not include leases executed and not yet commenced as of , with total estimated future undiscounted lease obligations of approximately $ . of which approximately $ is expected to be paid in the next 12 months. Generally, these lease obligations will commence between 2026 and 2028, , with lease terms ranging from less than one year years to 20 years.

In addition, the table above does not reflect commitments entered into after , with aggregate future minimum payment obligations of approximately $ . We also entered into contingent obligations after to purchase up to approximately $ of compute and infrastructure capacity that are subject to certain conditions, including the vendor obtaining qualifying financing or securing a facility lease, as applicable. We also entered into certain agreements after that are cancelable without penalty within one year with short term in nature. Minimum payments for the next 12 months under such contracts of are approximately $ . See Note 17 to our consolidated financial statements included elsewhere in this prospectus for more information on commitments entered into subsequent to .

Approximately $ of our contractual obligations are expected to be paid in the next 12 months.

Consistent with our compute and data center strategy, we expect to continue to enter into additional long-term arrangements to secure compute and infrastructure capacity, and to make significant related investments as we scale our business.

The following describes certain of our most significant existing arrangements. We are also party to other compute infrastructure service arrangements and leases that are not described below.

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In November 2025, we entered into an agreement with Microsoft, which was subsequently amended in February and October 2026, pursuant to which we committed to spend an aggregate of at least $31.4 $44.9 billion between November 2026 and May 2033, regardless of actual usage. Our commitment under such agreement is non- cancelable non-cancelable except in the event of Microsoft s uncured material breach or, on a per-tranche basis, for undelivered tranches.

In March 2026, we entered into an agreement with Google, which was subsequently amended in between May and August 2026, and pursuant to which we committed to spend an aggregate of at least approximately $111.1 $114.5 billion between April 2026 and July 2033, regardless of actual usage. If our actual spend falls short, we must pay Google the difference as a true-up subject to certain adjustments and exceptions if available. Our commitment commitments under such agreement is are non-cancelable except in the event of Google s uncured material breach. In addition, we also committed to procure additional TPU compute from TPU providers, including Google, to be delivered between 2028 and 2031. The payment obligations for such additional compute are determined by the capacity made available, the manner in which it is deployed, the pricing mechanics, and the satisfaction of certain deployment conditions. We estimate the aggregate future payments for such additional compute to be approximately $125.0 billion to $150.0 billion, which are not included in the contractual commitments table above.

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In Between May and July October 2026, we entered into and amended several agreements with SpaceX.AI LLC (formerly known as X.AI LLC) ( x.AI SpaceXAI ), a wholly owned subsidiary of Space Exploration Technologies Corp. (collectively, x.AI the SpaceXAI Arrangements ), one of which was subsequently amended in June 2026, to access compute powered by NVIDIA GPUs. Under the x.AI SpaceXAI Arrangements, we agreed to spend an aggregate of up to $84.5 $120.5 billion over terms extending into 2029, consisting of approximately $2.37 $3.1 billion in the aggregate per month under the agreements once all capacity has been delivered, which we expect in December 2026 , with different fees during capacity ramping periods. at reduced fees. Following initial non-cancelable non- cancelable periods ending in August 2026 for the May agreements and January 2027 for and March 2027 under the July agreement, respective agreements, each agreement may be cancelled by either party upon 90 days advance written notice.

Under the Hardware Supply Agreement with AMD, we committed to obtain an initial tranche of compute capacity in calendar year 2027 by purchasing AMD-based Helios rack-scale systems from approved manufacturers or by accessing such systems through third-party service providers, provided certain conditions related to deployment proposals are met. The agreement does not specify a fixed dollar commitment. If we procure the full amount of this initial committed capacity, we expect aggregate expenditures to exceed $20.0 billion over the term of the agreement, which are not included in the contractual commitments table above. The agreement also provides for the potential procurement of additional capacity of up to approximately the amount of our initial commitment. Our agreement with AMD is non-cancelable by us except in the event of AMD s uncured material breach and will automatically terminate 12 months after both parties fulfill their commitments under the agreement and all ordered AMD GPU capacity has been delivered.

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As of June 30, 2026 , there was approximately $26.6 billion of total unrecognized stock-based compensation expense related to RSUs. Of that amount, $2.9 billion relates to RSUs for which the service-based vesting condition had been satisfied or partially satisfied. Following the completion of this offering, stock-based compensation expense related to our RSUs will result in increases in our expenses in future periods, in particular the quarter in which this offering is completed, as the performance-based vesting condition applicable to a significant portion of our outstanding RSUs will be satisfied upon the effectiveness of the registration statement of which this prospectus forms a part. Upon the completion of this offering, we will record cumulative stock-based compensation expense of approximately appr oximately $ related re lated to RSUs outstanding as of the date of this prospectus, for which (i) the service-based vesting condition is fully or partially satisfied as of such date and (ii) the performance-based vesting condition is satisfied upon the effectiveness of the registration statement of which this prospectus forms a part.

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The application of this methodology involves the use of complex and subjective estimates, judgments, and assumptions, including the probability and timing of each settlement scenario such as a qualified equity financing, initial public offering, direct listing, or change of control the estimated fair value of our equity securities into which the notes may convert the applicable conversion prices, which vary by note series and are contingent on factors such as elapsed time since issuance and contractual caps and percentage discounts and the ownership thresholds and rollover provisions that determine the extent to which principal balances convert into equity versus being reissued as rollover notes. In particular, the ownership cap and rollover mechanism whereby conversion is capped at specified ownership thresholds and any unconverted principal balance is re- issued as a non-interest bearing rollover note that remains subject to fair value measurement requires significant judgment in estimating what proportion of each note financing will convert versus roll over, because this determination depends on the size and structure of future equity financings that are inherently uncertain.

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Business 140 changes

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Anthropic was founded in 2021 by a team of researchers responsible for many of the breakthroughs that define AI. We are first and foremost a research lab our mission is the responsible development and maintenance of advanced AI for the long-term benefit of humanity . This mission directs our focus and, together along with our talent and culture, our frontier and safety research, our approach to compute, and our enterprise strategy, forms it is one of the core advantages that set us apart. These advantages enable us to continuously advance frontier AI and shape the standards for its safe and responsible development. Our frontier AI, Claude, is delivered to customers through our models, platform, and applications. Claude has experienced the fastest enterprise adoption of any technology in history, as demonstrated by revenue growing from $0 at commercial launch in the first quarter of 2023 to $ for the three months ended . September 30, 2026. This rapid and growing adoption generates two self- reinforcing self-reinforcing dynamics an improvement loop that advances Claude and an investment loop that helps fund our continued research in frontier AI.

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Frontier & Safety Research. We believe that sustained, focused research at the frontier of intelligence is required to build the most capable and safest AI systems. Our frontier AI capabilities and safety research are deeply integrated and directly shape model design, training, and deployment, helping us produce systems that are more reliable, steerable, and well-suited for real-world deployment, particularly in demanding enterprise environments. We translate our research leadership into innovation velocity, and have consistently released better models, platform capabilities, and applications. Each version of a Claude model is used to build assists in building the next, helping to compress development timelines and produce compounding improvements in the speed at which we innovate. We refer to this recursive dynamic as closing the loop, and we believe it is one of the most significant structural advantages in frontier A I and can greatly accelerate the rate at which capabilities advance.

We believe that model capabilities must be advanced together with safety, alignment, and security practices, particularly as the speed of AI development accelerates. We assess the risks of each model during development and before and after release, and take the steps we believe are appropriate to balance model capabilities with safety, alignment, and security, even where doing so may moderate the rate at which we release new capabilities. We view decisions of this kind as deliberate tradeoffs that we make because they serve the Company Purpose, the long-term interests of our mission, and our customers demand for safe and aligned models.

Our Approach to Compute . We procure manage compute as a single, fungible pool from multiple strategic partners, and we dynamically direct available compute between workloads based on where the marginal unit is expected to be most productive at any given time. We believe that this approach to compute enables us to deliver superior models, serve more customers, and achieve greater productivity from our compute investment. This compute efficiency creates the foundation for us to advance the frontier of AI capabilities through research and model development, meet growing demand from customers, and provide for internal usage of Claude. We have achieved this through our research breakthroughs and our multi-chip compute architecture across AWS Trainium, Google TPUs, NVIDIA GPUs, and AMD GPUs, enabling us to orchestrate workloads to optimize for price and performance. To support our research, model development, customer demand, and internal usage of Claude, we continue to invest at scale. As of , and subsequent to September 30, 2026, we have entered into purchase commitments and lease agreements, including short-term commitments, as well as leases not yet commenced, with an aggregate committed spend of more than $ , substantially all of which is related to compute and infrastructure. and we expect These commitments will continue include approximately $ expected to increase. See the section titled Management s Discussion and Analysis of Financial Condition be incurred before December 31, 2030, and Results substantially all of Operations Liquidity the remainder is expected to be incurred between 2031 and Capital Resources Contractual Obligations for more information. 2045.

Approximately $ of these commitments are due in the next 12 months. See the section titled Management s Discussion and Analysis of Financial Condition and Results of Operations Liquidity and Capital Resources Contractual Obligations for more information.

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The speed and depth of our enterprise customer adoption are powerful evidence of Claude s position at the frontier of AI. Our customer base as of September 30, 2026 includes More than 11,900 customers with $100,000 or more of revenue on a TTM basis More than 1,900 customers with $1 million or more of revenue on a TTM basis and Approximately 250 customers with $10 million or more of revenue on a TTM basis.

Claude is not Unlike a static product that serves a single use case, it Claude is frontier AI with rapidly advancing capabilities.

We build at three layers of the stack the models themselves, the platform for building on those models, and the applications that place Claude directly in the hands of our users. An advance at any layer compounds across all three layers, accelerating the pace at which we can deliver more capable intelligence. We believe the value of this integrated approach is reflected in the increasing number of customers that use both Claude Platform and our first-party applications. For the three months ended , % September 30, 2026, over 50% of our customers with $100,000 or more of revenue on a TTM basis used Claude Platform and at least one of our first-party applications, up from % approximately 30% for the three months ended . December 31, 2025.

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Building and scaling frontier AI is one of the most important and capital-intensive endeavors in history. Our financial model provides us with the following strengths that allow us to build and scale efficiently Rapid Revenue Growth. Our enterprise strategy is designed to drive durable customer adoption by embedding Claude directly into business-critical workflows and enabling the development of products built on Claude. We believe that enterprise customers achieve a compelling return on investment from Claude, as agentic workflows can drive both top-line growth and efficiency. This enables us to expand quickly with customers, as demonstrated by our Net Revenue Retention of % approximately 900% as of . September 30, 2026.

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Operating Efficiency . Our operating efficiency, derived from our high talent density, our efficient go- to-market, and how extensively our teams leverage Claude in their work, enables us to scale with a smaller team relative to other large enterprise technology companies. Our operating efficiency is demonstrated by TTM revenue per employee of $ over $6.6 million as of , September 30, 2026, compared to $ $1.4 million as of . September 30, 2025.

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The demonstrated growth, scale, and efficiency of our financial model help us to continue making significant long-term investments to build frontier AI responsibly. Our business trajectory and financial profile have enabled us to access capital and secure compute from investors and partners. As of June 30, 2026, we have had raised an aggregate of $141.1 billion of capital and have had cash and cash equivalents of $112.4 billion and short- term investments of $19.3 billion . Long-term investments come with risks, as we must predict compute needs multiple years into the future. However, we believe our compute efficiency positions us to amplify returns if demand is greater than our forecast and can provide financial resilience if demand is lower or arrives later than we anticipate.

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A clear example of our ability to close the loop is the deployment of Claude Code, our agentic coding product, across our engineering organization. As our models have advanced, we have seen significant improvement in Claude s capability on more challenging, open-ended engineering problems that lack a clear specification and have historically depended on experienced human judgment. Claude s success rate on these problems reached an average of % in , up percentage points in months, based on our internal benchmarks.

A clear example of our ability to close the loop is the deployment of Claude Code, our agentic coding product, across our engineering organization. As our models have advanced, we have seen significant improvement in Claude s capability on more challenging, open-ended engineering problems that lack a clear specification and have historically depended on experienced human judgment. Claude s success rate on these problems reached approximately 90% in September 2026, up approximately 50 percentage points in nine months, based on our internal benchmarks. Claude Code has progressed from suggesting code to writing and running it directly and working autonomously over long time horizons on complex, multi-step engineering tasks. This has enabled our engineers to increasingly direct and review its work rather than write code line by line. As a result, the average daily volume of code contributed to our codebase per engineer in the three months ended September 30, 2026 was over 45 times the average daily volume in the year ended . % December 31, 2024. Over 90% of the contributions to our codebase in September 2026 were written by Claude .

The impact of Claude extends beyond research and engineering. From December 31, 2024 to , September 30, 2026, our headcount grew over five times, while our revenue for the three months ended September 30, 2026 was 86 times our revenue for the three months ended December 31, 2024 .

We believe this operating leverage has been driven by the use of Claude throughout our organization. Across our research, engineering, go-to-market, and operations teams, Claude allows each of our employees to leverage a team of agents in their daily work, enabling a comparatively small team to take on work that would traditionally require a far larger one by multiplying the impact of each person.

The expansion of our own use of Claude reflects this leverage directly. The value of our own internal Claude usage at list prices has grown by over 250 times from January 2026 to , September 2026, and in , April 2026, this monthly value first exceeded our monthly personnel expense, excluding stock-based compensation. Because each version of Claude is used to help build the next and because Claude makes our teams more productive across the company, we believe the compute we devote to internal usage compounds these gains, continuously accelerating our pace of development and further strengthening our leadership position.

Using AI to help build more capable AI could also pose a considerable safety risk, particularly if it sharply accelerates the pace of progress. This is one of the areas covered by our Responsible Scaling Policy, which sets out our plans to monitor and mitigate the risks as we approach what has been termed recursive self- improvement.

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Our Near-Term Opportunity is to Transform Cognitive Work

Frontier AI is transforming cognitive work the application of knowledge, reasoning, and judgment to produce economic value. We believe it will make humans far more capable and expand the world s overall capacity for that work, including accelerating scientific discovery and helping businesses grow. Knowledge workers are the 6 See the section titled Industry, Market, and Other Data for a description of how we calculate annual economic value attributable to knowledge workers globally.

We expect AI capabilities across language, reasoning, mathematics, coding, scientific analysis, and an expanding range of agentic tasks and knowledge work to continue advancing for many years. As a result, we believe this will drive demand for AI that outstrips supply for the foreseeable future, limited principally by the availability of compute. We believe that the majority of this demand will be concentrated at the frontier our experience has been that enterprises gravitate to our most capable models across a wide variety of workloads, including their highest-value work. In addition, we believe that each successive expansion of the frontier will unlock new categories of work that, in turn, will generate the majority of incremental industry demand. We expect 6 See the section titled Industry, to continue increasing investment in compute, research talent, Market, and engineering resources to advance the frontier of AI. Within this framework, research labs with proprietary training methods, strong Other Data quality, and differentiated research talent are well-positioned for a description of how we calculate annual economic value attributable to outpace what scale alone would predict. knowledge workers globally.

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9 IQVIA Institute for Human Data Science, Global Medicine Use Trends 2026, February 2026.

including their highest-value work. In addition, we believe that each successive expansion of the frontier will unlock new categories of work that, in turn, will generate the majority of incremental industry demand. We expect the industry to continue increasing investment in compute, research talent, and engineering resources to advance the frontier of AI. Within this framework, research labs with proprietary training methods, strong data quality, and differentiated research talent are well-positioned to outpace what scale alone would predict.

A Near-Term Opportunity to Transform Cognitive Work

Frontier AI is transforming cognitive work the application of knowledge, reasoning, and judgment to produce economic value. We believe it will make humans far more capable and expand the world s overall capacity for that work, including accelerating scientific discovery and helping businesses grow. Knowledge workers are the leading edge of this opportunity. As frontier AI advances, more capable models can unlock entirely new use cases while also efficiently serving a wide range of cognitive work at scale across the capability-cost-speed curve. We believe the work that knowledge workers perform represented more than $40 trillion in economic value globally in 2025, 6 and with frontier AI s potential to make them meaningfully more productive, our near- term opportunity is to expand this value and accelerate economic growth. While it is still early to forecast frontier AI s full impact across the economy, IDC estimates that investment in AI solutions and services will yield a cumulative global economic impact of $22.5 trillion by 2031 . 7 We believe the impact could be even greater.

History suggests that transformative technologies expand the markets they enter. For example, information technology spend grew from approximately $1.2 trillion in 2006 to $4.3 trillion in 2025, a CAGR of approximately 7%, as cloud computing spend grew from zero to $1.9 trillion over the same period and expanded information technology budgets. 8 We have seen other technologies, including the personal computer, the internet, and the smartphone, grow their markets as well. The companies that built these technologies grew at a far faster rate than the economy as a whole. Global GDP grew from approximately $34 trillion in 2000 to more than $118 trillion in 2025 according to the World Bank, more than tripling. Over that same period, the ten largest publicly traded technology companies by market capitalization as of June September 30, 2026 grew their aggregate revenue from $75 $68 billion to more than $2.5 trillion, an increase of roughly 34 approximately 38 times, or approximately 10 11 times the rate of global GDP growth .

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Cybersecurity represents one of our most important near-term opportunities. As each new generation of AI models grows more capable of finding and exploiting vulnerabilities, we expect that defending enterprise networks and critical infrastructure will increasingly require frontier AI. At the same time, the diffusion of AI is expanding the threat surface, as organizations deploy agents and autonomous capabilities at an accelerating pace. Our leadership in coding has allowed us to advance Claude s cybersecurity capabilities and build products that help enterprises secure their most critical infrastructure. For example, Claude Security can continuously scan customers codebases, triage vulnerabilities, and write fixes. We also recently launched OSS Scanner, which extends some of these capabilities to the open-source projects that enterprise software is built on.

Through our trusted-access programs, vetted cyberdefenders can also use our most capable models for security 9 IQVIA Institute for Human Data Science, Global Medicine Use Trends 2026, February 2026.

operations, incident response, and authorized penetration testing, shifting security to a continuous protection model.

Over time, frontier AI We expect other sectors to follow as Claude s frontier capabilities may extend beyond current markets to open entirely new ones, reaching domains such as robotics, advanced manufacturing, and logistics, and accelerating progress in scientific research, including drug discovery and materials science. We are beginning to take a direct role in realizing this potential.

For example, in the life sciences sector, where annual global pharmaceutical spend is expected to exceed $2 trillion in 2026, 9 Claude is used in drug discovery and development by our customers, our biotechnology partners, and our own researchers. We are also extending Claude into robotics, where our MHS Model Hardware Standard enables AI agents to operate lab and manufacturing equipment such as microscopes, liquid handlers, and off-the-shelf robotic arms.

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We believe that frontier AI companies must invest in safety to help ensure the responsible diffusion of this technology. We also believe that safety and ethical behavior resonate particularly strongly with enterprises, where rigorous safeguards, predictable model behavior, and demonstrable accountability have become decisive criteria in selecting an AI partner for mission-critical workloads.

While the potential benefits of AI are extraordinary, its rapid advancement will impact the economy and society in ways that could create significant dislocation, disruption, particularly if the technology is not developed and deployed responsibly. For example, bad actors have already conducted high-profile cyberattacks using AI s capabilities to discover vulnerabilities, generate malware, and evade detection tools other risks associated with misuse, including in the domain of biology, could result in even greater harm. AI deployed at scale also has the potential to concentrate power and wealth both within and between countries in ways that could erode trust, harm society, and destabilize the geopolitical order. In addition, Misaligned AI systems could corrupt institutional decision-making, decision- making or cause large-scale harm through opaque autonomous actions that are not visible or unsteerable behavior, understandable to their users and erode operators. We believe that frontier AI companies must invest in safety and alignment to help ensure the trust responsible diffusion of this technology. We also believe that makes complex economic safety, alignment, and social systems function. ethical behavior resonate particularly strongly with enterprises, where rigorous safeguards, predictable model behavior, and demonstrable accountability have become decisive criteria in selecting an AI partner for mission-critical workloads.

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For example, in April 2026, we initially released our frontier model, Mythos, as a gated research preview through Project Glasswing, available to select organizations for cybersecurity applications, rather than making it broadly available at launch due to its advanced capabilities in cyber vulnerability discovery. We believe this clarity of mission reduces friction, accelerates decision-making, and fosters a culture where safety and capability are pursued with equal intensity. in tandem.

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We believe we have assembled the deepest concentration of AI research talent in the world, including many of the researchers who pioneered the techniques that underlie modern LLMs. Our founding team originated several foundational advances in AI, including Scaling Laws, GPT-2 and GPT-3, RLHF, and mechanistic interpretability. Our conviction that safety and capability must advance together helps us attract and retain world-class talent, including researchers and engineers. For example, we have experienced % approximately 1% regrettable attrition of our employee base overall in the TTM period ended . September 30, 2026.

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Our Safety Research Is a Commercial Benefit . As models take on agentic roles with access to critical business systems, trust and reliability are paramount. And as capabilities increase, the ability to operate safely becomes one of the key determining factors for commercial viability. Models that are well-aligned are better at following a user s instructions for example, they avoid taking potentially destructive actions without fully understanding user intent. They are also more robust against attacks such as prompt injection, where malicious actors attempt to hijack the model by feeding it illicit instructions. Our work in Constitutional AI and our Responsible Scaling Policy, on alignment, interpretability research, safeguards, red-teaming, and embedding independent evaluators to audit red-teaming, as well as the use of external reviewers who can assess our safety practices, help helps us create safer, more reliable models, and therefore position positions us to meet our customers rigorous requirements. Safety and capability research are integrated, which enables us to deliver the trust and performance required for enterprise workflows.

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of the same pattern in knowledge work such as scientific research, investment analysis, and insurance underwriting.

With each model and product advancement, Claude is able to address more valuable use cases, deepening its impact for existing customers while lowering the adoption threshold for new ones. When a model crosses the capability, reliability, and trust threshold required for a category of work, adoption in that category generally moves quickly from experimentation into production. Coding was the first such category within roughly a year, Claude progressed from suggesting individual lines of code to operating fleets of agents working autonomously across production codebases. Cybersecurity is following a similar curve, with Claude s performance on ExploitBench, a benchmark developed by Carnegie Mellon researchers that evaluates AI models ability to exploit software vulnerabilities, increasing from 40% with Opus 4.8, to 78% with Claude Mythos Preview 5, and now Mythos 5.1 helping to 91% with Opus 5.5 over a period of approximately four months. Cyberdefenders identify are now identifying and patch patching vulnerabilities at scale. We are also seeing early evidence 10 IDC, Worldwide Developer Population Growth Forecast, 2025 2029, doc # US53789825, September 2025. expect these improvements in model capabilities to unlock additional use cases.

Claude Security and our recently launched OSS Scanner are early examples, providing the ability to scan codebases on a continuous basis and propose fixes before attackers find vulnerabilities.

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We refer to these AI systems that work alongside humans to perform complex, multi-step work at professional levels as Virtual Collaborators. Virtual Collaborators carry the access rights, system connections, and context needed that their organizations grant them, which allows them to function more accurately and reliably. They can navigate and use internal tools and execute workflows that span multiple steps that require sustained reasoning. Virtual Collaborators are AI designed to be embedded where work gets done, and our aim is to continue extending them to knowledge workers globally, a population that is estimated to exceed one billion in 2028. 10 Claude Code The clearest manifestation of Virtual Collaborators today is Claude Code, our coding agent and the product we believe has most concretely defined what autonomous AI work looks like. Claude Code shifted the market s understanding of what an AI system could do alongside a software IDC, Worldwide Developer it not only suggests the next line of code, but also plans, writes, tests, and debugs all the way to production-grade code that is ready to ship. Population Growth Forecast, 2025 2029, doc # US53789825, September 2025.

continue extending them to knowledge workers globally, a population that is estimated to exceed one billion in 2028. 10 Claude Code The clearest manifestation of Virtual Collaborators today is Claude Code, our coding agent and the product we believe has most concretely defined what autonomous AI work looks like. Claude Code shifted the market s understanding of what an AI system could do in collaboration with software developers the model suggests the next line of code and goes further by planning, writing, testing, and debugging a process that results in production-grade code. Within months of its release, autonomous coding became the reference point for measuring the progress of frontier AI. For enterprise AI use cases, we believe the launch of Claude Code was comparable in its impact to the introduction of the first widely adopted conversational AI assistants. What makes Claude Code a Virtual Collaborator is its sustained reasoning, a harness that translates intent into actions, a sandboxed virtual an execution environment that maintains a persistent state whether on a developer s machine or in a sandboxed cloud environment, integration with existing tools and systems, and a user-friendly interface. Its uses are highly varied and often surprising for example, NASA engineers used Claude Code to plan write, and execute write navigation commands for the Mars Perseverance rover, resulting in the first AI- planned AI-planned drive on Mars.

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All digital work is ultimately an expression of code, and Claude s mastery of it powers Virtual Collaborators capable of handling complex work far beyond software development. Claude Cowork extends the same agentic architecture of Claude Code to knowledge workers broadly by translating a user s intent into completed work, autonomously reading files, navigating applications, and executing multi-step workflows on a user s desktop while the underlying code is abstracted away. By extending beyond Claude Code with applications purpose-built for specific professions and industry verticals, we accelerate Claude s diffusion into new categories of knowledge work and deepen our presence across the enterprise. As of , September 30, 2026, adoption of Claude Cowork, which we made available as a research preview in January 2026, outpaced the adoption that Claude Code achieved at the equivalent point following its research preview release in February 2025. In September 2026, we began merging Claude Cowork and Claude.ai, bringing agentic and conversational work into a unified application. Users can now move from a simple question to complex, multi-step tasks in the same conversation.

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Our commitment to our mission instills confidence in our customers to choose Claude as a trusted partner. Our investments in alignment research on AI alignment, interpretability, cybersecurity, and enterprise-grade controls aim to deliver the predictability and dependability that organizations need in customer-facing and regulated contexts. This trust expands the scope of work that enterprises delegate to Claude and the systems into which they integrate Claude. Enterprises are aligning their strategies around Claude with confidence that we are building frontier AI to serve their needs for the long term.

This trust means that enterprises can expand the scope of the work that they delegate to Claude, as well as the systems into which Claude is integrated. Enterprises are aligning their strategies around Claude with the confidence that we are building frontier AI that serves their needs in the long term.

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We seek to bring Claude to every corner of the economy at whatever level of autonomy each task demands, from a single suggestion to an agent that runs unsupervised independently for hours. Achieving this goal requires more than a capable model. The most demanding deployments need intelligence that is reliable, connectable, and deployable within the specific data environments, regulatory constraints, and workflow patterns of each organization. The Intelligence is one limiting factor, for a use case may not just be intelligence, but so are connectors that do not yet exist, governance frameworks that are not yet written, and orchestration logic that must needs to be built from scratch. Our platform seeks to close these gaps, and we believe the breadth and speed with which we have done so is a primary reason customers build on Claude.

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Applied AI Teams . Our Applied AI teams embed more deeply with select customers, building solutions that make it easier for organizations to benefit from Claude s intelligence. They work with enterprises to design and deploy custom solutions, specialized workflows, and domain-specific implementations tailored to the customer s own requirements. This work not only drives deeper adoption within individual customers but also and generates the feedback and use cases information from users that help to shape our platform and product roadmap. Our direct and Applied AI teams work together as a hybrid sales and engineering function, organized by geography and then by industry so that they bring domain expertise to each customer.

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Ecosystem Partnerships . Major global SIs have built dedicated Claude practices with teams trained to deploy our platform and applications. Go-to-market alliances with leading data platforms embed Claude into data infrastructure that enterprises already operate, facilitating adoption of Claude within existing workflows and making it easier for enterprises to realize value from Claude. To accelerate the growth and capability of this ecosystem, in March 2026, we launched the Claude Partner Network, committing an initial $100 million in 2026 to fund partner training, technical certification, and joint market development with the firms that bring Claude into enterprise environments. As of September 30, 2026, this network comprises over 150,000 practitioners across over 4,000 organizations who have received certifications through our Claude Certification Program. Certifications represent role-specific 11 Run-Rate Revenue is an operating metric, is not a substitute for revenue prepared in accordance with GAAP, and is not a forecast of future revenue. Because consumption-based revenue represents the substantial majority of our revenue and may fluctuate from period to period, and because our Run-Rate Revenue growth rate is expected to decline over time, our Run-Rate Revenue as of any measurement date may not be indicative of our revenue for future periods. Our Run-Rate Revenue as of any measurement date has included, and we expect will continue to include, amounts from customers that we subsequently determine are using our models, platform, and applications in violation of our usage policy or commercial terms, and whose revenue would not be expected to recur following restriction or termination of their access. See the section titled Risk Factors Certain of our operating metrics are subject to assumptions and limitations. As a result, these metrics may not provide an accurate indication of our actual performance or future results for additional information.

Ecosystem Partnerships . Major global SIs have built dedicated Claude practices with teams trained to deploy our platform and applications. Go-to-market alliances with leading data platforms embed Claude into data infrastructure that enterprises already operate, facilitating adoption of Claude within existing workflows and making it easier for enterprises to realize value from Claude. To accelerate the growth and capability of this ecosystem, in March 2026, we launched the Claude Partner Network, committing an initial $100 million in 2026 to fund partner training, technical certification, and joint market development with the firms that bring Claude into enterprise environments. This network comprises consultants across organizations who have received certifications through our Claude Certification Program. Certifications represent role-specific capabilities validated through proctored examinations designed to give enterprises confidence in the partner they are selecting . In October 2026, we launched the Claude Frontier Academy (the Academy ), backed by a $100 million commitment, to address a key constraint on enterprise AI adoption the shortage of engineers who can take AI from an initial use case into production. Drawing on our own experience deploying Claude inside large enterprises, the Academy trains our customers and partners engineers to the same standard as our own engineers, with each participant leading a Claude deployment at their own organization. We aim to train 10,000 engineers through the Academy by the end of 2027, beginning with cohorts from leading consulting firms and enterprises.

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We believe the diffusion of AI through the global economy represents one of the largest opportunities in history to improve how humans live and work, and it is just beginning. As of , September 30, 2026, our customers with $100,000 or more of revenue on a TTM basis included % every company in the Fortune 10, over 50% of the Fortune 500, and % over 30% of the Global 2000. Within the Fortune 500, these customers included of the 10 largest software and IT services companies, of the 10 largest internet companies, nine of the 10 largest pharmaceutical companies, of the 10 largest banks, nine of the 10 largest semiconductor companies, and eight of the 10 largest healthcare companies. We believe enterprises are still in early phases of deployment, and we believe most knowledge workers have yet to fully experience what frontier AI can help them accomplish. We believe many industries have barely begun to explore the transformative potential of AI-native workflows. Furthermore, each successive version of a Claude model is designed to unlock new use cases, new customer types, and entirely new categories of economic value and expand our addressable market.

Furthermore, each successive version of a Claude model is designed to unlock new use cases, new customer types, and entirely new categories of economic value and expand our addressable market.

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11 Run-Rate Revenue is an operating metric, is not a substitute for revenue prepared in accordance with GAAP, and is not a forecast of future revenue. Because consumption-based revenue represents the substantial majority of our revenue and may fluctuate from period to period, and because our Run-Rate Revenue growth rate is expected to decline over time, our Run-Rate Revenue as of any measurement date may not be indicative of our revenue for future periods. Our Run-Rate Revenue as of any measurement date has included, and we expect will continue to include, amounts from customers that we subsequently determine are using our models, platform, and applications in violation of our usage policy or commercial terms, and whose revenue would not be expected to recur following restriction or termination of their access. See the section titled Risk Factors Certain of our operating metrics are subject to assumptions and limitations. As a result, these metrics may not provide an accurate indication of our actual performance or future results for additional information.

Our enterprise strategy is designed to drive durable customer adoption by embedding Claude directly into business-critical workflows and enabling the development of products built on Claude. Over the past three years, we have seen rapid customer adoption across companies of every size and industry around the world.

From September 30, 2025 to , September 30, 2026, we have grown customers with $100,000 or more of revenue on a TTM basis from more than 950 to . more than 11,900. Additionally, o ur Run-Rate Revenue was $ as of . October 31, 2026. 11 Significant Customer Expansion Our customers journey using Claude often begins with a single use case before expanding across departments, applications, and workflows. As our models become more capable, customers often deepen our partnerships they find more ways to embed Claude into their workflows, increasing the scope of what Claude can accomplish within their enterprises. This pattern of initial deployment, demonstrated value, and rapid expansion has been replicated across organizations and is reflected in our Net Revenue Retention of % approximately 900% as of . September 30, 2026.

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Diffusion also accelerates as our models get more capable and more efficient allowing us to pass on a portion of our compute efficiency gains by lowering costs for customers. With the release of Claude Fable 5.1 in September 2026, we reduced the cost for typical workloads versus earlier Fable 5 by approximately 25%, with savings up to 45% for complex coding and highly agentic tasks. With the release of Opus 5.5 in September 2026, we reduced customer costs compared to earlier Opus 5 by approximately 40%. We have been able to make these improvements while preserving our margins due to our compute efficiency. We have historically seen customers expand their usage in response to higher capability and lower cost per task. For example, when we reduced customer costs on Claude Opus 4.5 relative to Opus 4.1 by approximately 67% in November 2025, our quarter-over-quarter revenue growth accelerated from 48% for the three months ended December 31, 2025 to 132% for the three months ended March 31, 2025.

Diffusion also accelerates as we deliver value to our customers by unlocking new capabilities and by delivering existing capabilities at a lower cost per task. Customers cost per task can decrease for two reasons newer, more capable model versions can complete tasks more efficiently, and we may reduce the prices we charge for our models. For example, with the release of Claude Fable 5.1 in September 2026, we reduced the cost of typical workloads by approximately 25% compared to Fable 5, with savings of up to 45% for complex coding and highly agentic tasks. Similarly, with the release of Opus 5.5 that same month, we reduced customers cost per task by approximately 40% compared to Opus 5. In each case, the reduction was a combination of a lower price and improved efficiency, the contributions of which depend on the task. Because of our compute efficiency, we have been able to make these improvements while preserving our margins.

In the past, when we have launched new model versions that deliver a significant increase in capability and a lower cost per task, we have generally seen customers expand their use of our intelligence service. For example, we launched Opus 4.5 in November 2025 with greater capabilities and a lower price and cost per task than its predecessor Opus 4.1. Following that launch, our total quarter-over-quarter revenue growth accelerated from 48% for the three months ended December 31, 2025 to 132% for the three months ended March 31, 2026 . This growth reflected the combined effect of several factors. These included lower prices and improved capability that unlocked new use cases, the emergence of new products, and expanded customer adoption. More recently, in September 2026, we launched Opus 5.5, which delivered a significant increase in capability and a lower cost per task compared to previously available models, and many customers have since migrated to it from older models.

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High Talent Density. As of , September 30, 2026, with approximately 5,300 employees, our TTM revenue per employee was $ over $6.6 million a reflection of what we believe is the deepest concentration of AI research talent in the world. We cultivate a low- ego, low-ego, high-impact, and mission-aligned culture that minimizes friction, which we believe results in an organization that produces output disproportionate to its headcount.

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Claude is embedded in workflows across all teams, providing a substantial increase in the overall productivity of our organization, with each new model version accelerating this effect.

Internal Usage of Claude . Our operating efficiency reflects the structural advantages of an organization that is one of the most intensive users of its own technology. For example, % over 90% of the contributions to our codebase in September 2026 were written by Claude. Additionally, the average daily volume of code contributed to our codebase per engineer in the three months ended September 30, 2026 was over 45 times the average daily volume in the year ended . December 31, 2024. Claude is embedded in workflows across all teams, providing a substantial increase in the overall productivity of our organization, with each new model version accelerating this effect.

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To support our research, model development, customer demand, and internal usage of Claude, we continue to invest at scale. As of , and subsequent to September 30, 2026, we have entered into purchase commitments and lease agreements, including short-term commitments, as well as leases not yet commenced, with an aggregate committed spend of more than $ . These commitments include approximately $ expected to be incurred before December 31, 2030, and substantially all of which the remainder is related expected to compute and infrastructure, be incurred between 2031 and we expect 2045. Approximately $ of these commitments will continue to increase. are due in the next 12 months. See the section titled Management s Discussion and Analysis of Financial Condition and Results of Operations Liquidity and Capital Resources Contractual Obligations for more information.

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Extend the Frontier into New Markets . As frontier AI continues to advance, we see potential for it to accelerate novel discoveries and open entirely new markets, reaching domains from healthcare and life sciences to robotics and the physical world. For example, in the life sciences sector, where annual global pharmaceutical spend is expected to exceed $2 trillion in 2026, Claude is used in drug discovery and development by our customers, our biotechnology partners, and our own researchers . 12 We are building AI agents that support scientists at each stage of that process. To build the best tools for the industry, we have invested in deep life sciences expertise of our own, hiring industry experts, building a wet molecular biology lab, acquiring Coefficient Bio, and partnering with industry leaders. Beyond knowledge work, we believe frontier AI has the power to transform physical work. Advances in Claude s general capabilities, together with our MHS, now allow it to operate lab and manufacturing equipment such as microscopes, liquid handlers, and off-the-shelf robotic arms. We believe that compounding model capabilities will continue to unlock transformative opportunities across many other sectors of the global economy.

Beyond knowledge work, we believe frontier AI has the power to transform physical work. Advances in Claude s general capabilities, together with our Model Hardware Standard, now allow it to operate lab and manufacturing equipment such as microscopes, liquid handlers, and off-the-shelf robotic arms.

We believe that compounding model capabilities will continue to unlock transformative opportunities across many other sectors of the global economy.

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Our platform unifies frontier intelligence with the harnesses, connectors, governance, and orchestration that are all required to put that intelligence into production. As customers build on our the primitives we provide, Claude becomes woven into an integral part of their data, workflows, and institutional knowledge, and the relationship deepens with each integration. We open our platform to all builders because we believe enabling a wide range of companies to build on Claude generates more innovation and value than we could create on our own.

We build first-party applications to demonstrate where frontier models are heading and to deliver fully integrated solutions where we have a distinct viewpoint on the workflow. Applications like Claude Code and Claude Cowork serve as reference architectures for are early examples of what the future of agentic work putting might look like they put our latest AI capabilities directly into the hands of users while accelerating the market s understanding of what is possible. Because our research and product teams work side by side, new model capabilities inform our products, and how customers use those products informs how we train our models. This allows us to build products for where we believe model capabilities are going, not just where they are today. For example, we designed Claude Code around the agentic coding capabilities we expected our models to achieve, which positioned it to scale rapidly as those capabilities arrived, and we have taken a similar approach with Claude Cowork. AI s possibilities.

Because our research and product teams work side by side, new model capabilities inform our products and customer feedback on those products informs our research priorities. This allows us to build products for where we believe model capabilities are going, not just where they are today. For example, we designed Claude Code around the agentic coding capabilities we expected our models to achieve, which positioned it to scale rapidly as those capabilities arrived. We have taken a similar approach with Claude Cowork.

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Mythos (including Fable) . Our most capable model class, delivering frontier performance across all domains and solving problems AI has not reliably handled before, especially in coding and long- running agentic tasks. Given its advanced capabilities in sensitive areas like software vulnerability discovery and biology, we deploy this underlying model in two distinct configurations. Fable is generally available and runs with our production safeguards, which route a small share of requests block or limit performance on certain sensitive topics, including by routing requests to a less capable Claude model. rather than declining them outright. Mythos runs with safeguards calibrated for vetted organizations and individuals doing cybersecurity and life-sciences life sciences work, and is available only through our trusted-access programs, including Project Glasswing. We first made the class available in April 2026 as Claude Mythos Preview through Project Glasswing, more broadly released Mythos 5 and Fable 5 in June 2026, and released Mythos 5.1 and Fable 5.1 in September 2026. our Cyber Verification Program.

We first made the class available in April 2026 as Claude Mythos Preview through Project Glasswing, made Fable 5 generally available and offered Mythos 5 to Project Glasswing participants in June 2026, and released Mythos 5.1 and Fable 5.1 in September 2026.

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Long Context . Claude supports large context windows and sustains maintains its strong performance even as inputs grow, so meaning that developers can pass include entire codebases, large document sets, or long agent histories in a single request.

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Model Hardware Standard . Currently in research preview, MHS our Model Hardware Standard enables AI agents to find, understand, and safely operate lab and manufacturing equipment such as microscopes, liquid handlers, and off-the-shelf robotic arms. MHS Our Model Hardware Standard is model-agnostic and lets any agent harness reach devices with a programmable interface through standard protocols such as MCP.

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Claude.ai delivers top-of-funnel demand generation for enterprise adoption. As of In September 2026, we began merging Claude Cowork is integrated within and Claude.ai into a unified application, such that any request is automatically handled using the appropriate tools, drawing on Claude Cowork s capabilities.

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Customers in regulated industries and beyond use our most capable models for sensitive work. These customers must keep their data private, and we must be able to detect misuse. In September 2026, we announced Enterprise Frontier Safeguards, which is designed to address both needs. The activity data we use for automated safety monitoring is stored in the customer s own cloud account, under the customer s encryption keys and access controls. Our automated systems review recent activity for signs of serious misuse and they send alerts of such misuse directly to the customer s security team. No review by Anthropic employees is required. We developed Enterprise Frontier Safeguards with more than 100 customers in industries including financial services, healthcare, and the public sector. We are rolling out this feature in phases and, until the completion of the rollout, eligible customers receive zero data retention on Fable 5 and Fable 5.1, meaning we do not keep their inputs or outputs after we process a request.

We developed Enterprise Frontier Safeguards with more than 100 customers in industries including financial services, healthcare, and the public sector. We are rolling out this feature in phases and, until the completion of the rollout, eligible customers receive zero data retention on Fable 5 and Fable 5.1, meaning that, except where needed to comply with applicable law or combat misuse or harm, we do not store their inputs or outputs after we process a request.

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Claude for Financial Advisors . Provides financial advisors and wealth management firms with pre- built, customizable workflows for common advisory workflows, tasks, such as preparing for client meetings, drafting follow-ups, reviewing portfolio rebalances, and preparing estate and tax briefs. Claude for Financial Advisors plugs directly into the systems advisors already use (e.g., custodial platforms, portfolio management and financial planning tools, and customer relationship management software), with advisor review built into each workflow to help firms meet their compliance requirements.

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Claude for Education. Provides trusted AI solutions for higher education institutions and K-12 educators. Claude for Higher Education gives faculty, students, researchers, and administrators an AI partner for teaching, learning, research, and operations. This includes a learning mode for students, which is designed to strengthen critical thinking. rather than hand over solutions. Claude also helps university faculty across tasks such as research, drafting assignments, and supporting administrative work, all with the security and compliance built for institutional requirements. Claude for Teachers gives verified K-12 educators in the United States free access to premium Claude capabilities, a library of teaching skills, and a direct connection to evidence-based curricula, mapped to academic standards in all 50 states. Claude helps with the paperwork, so teachers can spend more time with their students.

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NVIDIA GPUs. Our strategic partnership with NVIDIA Corporation ( NVIDIA ), together with our arrangements with Microsoft, x.AI, SpaceXAI, Nscale, Lambda, and other cloud providers, provides us with access to compute capacity powered by NVIDIA GPUs, including NVIDIA Grace Blackwell and Vera Rubin GPU systems, as well as the opportunity to collaborate directly with NVIDIA on design and engineering to optimize future NVIDIA hardware for our workload profile.

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This transition is driven in part by the scale of our compute requirements as well as the potential long-term economic advantages of direct infrastructure leasing and hosting. Our first data center facility became operational this year.

Historically, we purchased compute under fixed-time agreements. As our compute requirements have scaled, we have transitioned to a hybrid model in which, in addition to purchasing compute as a cloud service, we also lease procure specialized AI accelerators directly and host operate this hardware in dedicated data center facilities leased and operated on our behalf, to our specification. We refer to this additional source of compute as Anthropic Direct. This transition is driven in part by the scale of our compute requirements as well as the potential long- term economic advantages of direct infrastructure leasing and hosting. Our first data center facility became operational this year.

Anthropic Direct also lets us separate our commitment to data center capacity from our commitment to the AI accelerators deployed inside it. Because data centers require longer lead times but represent a smaller fraction of total compute costs, this approach enables us to secure physical data center capacity early while deferring larger accelerator investments until our specific compute needs are more certain.

Our data center infrastructure strategy includes several contractual arrangements that, taken together, form a new source of compute to supplement the capacity we procure from our CSPs. Such arrangements include the following Compute Infrastructure Equipment. We procure specialized AI accelerators and associated components, including CPUs and high-bandwidth memory, through master equipment leases, including the 2026 Lease Arrangement, pursuant to which we receive such hardware for deployment in dedicated data center facilities operated by others on our behalf. See the section titled Management s Discussion and Analysis of Financial Condition and Results of Operations Liquidity and Capital Resources Contractual Obligations Infrastructure Equipment Leases for more information regarding the terms of these leases.

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As of , September 30, 2026, our customers with $100,000 or more of revenue on a TTM basis included % every company in the Fortune 10, over 50% of the Fortune 500, and % over 30% of the Global 2000. Across industries, enterprises deploy Claude in mission-critical production workflows for example, underwriting insurance policies, authoring writing clinical study reports for life-saving drugs, detecting and remediating cybersecurity threats, and analyzing portfolios for asset managers. Claude has achieved particularly deep adoption in highly regulated sectors where the cost of unreliable AI is prohibitive and trust cannot be retrofitted.

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Our governance structure and its goals 53 changes

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As the sole holder of Class T common stock, the LTBT generally has the authority to elect and remove the Class T directors, who together will constitute a majority of the authorized members of our board of directors. The Our Class T common stock will not vote on the election or removal of directors elected by the holders of our Class A common stock and Class F common stock, who will be elected or removed solely by the holders of Class A common stock and Class F common stock, voting together. For a discussion of the members of our board of directors who are currently Class T directors and those that will be Class T directors upon the completion of this offering, see the section titled Management Board of Directors.

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With respect to one of the Class T director seats (the Specified Class T Director ), the LTBT s ability to nominate that director, to remove that director without cause, or to change the director designated as the Specified Class T Director is subject to the concurrence of our NGC. If our NGC does not concur with such nomination, removal, or change in designation within 15 days of receiving notice, the matter will be submitted to a vote of the holders of our Class E common stock unless the LTBT elects to withdraw the notice. If submitted to a vote of the holders of Class E common stock, approval of the LTBT s proposal will require a majority of the votes cast by the our Class E common stock (subject to a quorum of a majority of the our outstanding Class E common stock). The LTBT may withdraw any notice of nomination, removal, or change in designation at any time before the taking of such a vote. Any Class T director, including the Specified Class T Director, may be removed for cause caus e, which will be determined in accordance with Delaware law, without the concurrence of our NGC or the approval of the holders of our Class E common stock provided, however, that each of the LTBT and the Founder LLC has agreed to provide 30 calendar days notice to the other stockholder and the NGC prior to effecting a removal of any director for cause.

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The terms of the LTBT and the rights of the our Class T common stock may be amended as follows (any of which, the Trust Amendment Threshold ) if the Trustees are voting in favor of such amendments, upon approval of 80% of the authorized members of our board of directors and 80% of the Trustees then in office (in each case, rounded up or down to the nearest whole number (any exact 0.5 rounding up)) if the our Class F common stock remains outstanding and the Trustees are not voting in favor of such amendments until the third anniversary of the completion of this offering, upon approval by (i) the our Class F common stock acting pursuant to the unanimous approval of the Continuing Founders, (ii) a majority of the votes cast by the our Class E common stock (subject to a quorum of 40% of the outstanding Class E common stock), and (iii) a majority of the votes cast by the our outstanding Class A common stock (subject to a quorum of a majority of outstanding Class A common stock) or at any time, upon approval by (i) the our Class F common stock acting by decision of 66 2 3% of the Continuing Founders (rounded up to the nearest whole number), (ii) 75% of the votes cast by the our Class E common stock (subject to a quorum of a majority of outstanding Class E common stock), and (iii) a majority of the votes cast by the our Class A common stock (subject to a quorum of a majority of outstanding Class A common stock) or if no Class F common stock remains outstanding and the Trustees are not voting in favor of such amendments, upon approval of 85% of the our outstanding shares of Class A common stock.

In addition, the our Class T common stock may be redeemed by us for no consideration upon approval of persons comprising the above thresholds for amendments of the terms of the LTBT or the rights of the our Class T common stock.

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The LTBT is governed by five Trustees. The Trustees have the authority to appoint the Trustees by majority vote of the Trustees then in office and to remove the Trustees by majority vote of the total number of authorized Trustees or by the unanimous approval of the other Trustees then in office and the approval of the NGC, provided that the LTBT must provide at least 30 days prior written notice to our NGC before effecting any such appointment or removal. The notice period is waivable by our NGC in its discretion. Trustees may also be removed by order of the Court of Chancery of the State of Delaware upon petition by a person designated by the Trust Agreement as having the power to enforce the agreement if a Trustee has engaged in disqualifying conduct and removal would best serve the purpose of the LTBT. Trustees will serve annual term s, and there is no limit to the number of terms a Trustee may serve. Trustees are selected based on their expertise in areas relevant to the LTBT s purpose, including AI safety, national security, public policy, social enterprise, and related fields. In practice to date, the Trustees and company executives have collaborated closely on sourcing, interviewing, and selecting Trustees. Of the five authorized seats for Trustees, two are one is currently vacant.

Dr. Neil Buddy Shah has served as a Trustee and Chair of the LTBT since June 2023. Dr. Shah will also serve as an initial manager of the Anthropic Public Benefit Entity. Fund. Dr. Shah has served as Chief Executive Officer of the Clinton Health Access Initiative ( CHAI ), a global health organization focused on improving access to health services in low- and middle-income countries, since June 2022. Prior to joining CHAI, Dr. Shah served as Managing Director of GiveWell, a nonprofit organization focused on directing charitable capital to cost-effective global health and development programs, and, before that, as co-founder and Chief Executive Officer of IDinsight, a global advisory, data analytics, and research organization. Dr. Shah serves on the boards of Prevail Fund, the Institute to End Mass Incarceration at Harvard Law School, Educate Girls, Giving Green, and IDinsight. He holds an A.B. in Economics from Harvard University, an M.D. with an emphasis in global health policy from Albert Einstein College of Medicine, and an M.P.A. in International Development from Harvard Kennedy School of Government.

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Mr. Fontaine was selected to serve as a Trustee because of his extensive background in foreign policy and national security, and foreign policy he will address the growing intersection between AI capabilities and geopolitical risks.

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Dr. Christopher Stubbs has served as a Trustee since October 2026. Dr. Stubbs is the Samuel C. Moncher Professor of Physics and of Astronomy at Harvard University, where he has been a member of the faculty since 2003. At Harvard, he served as Senior Advisor for AI to the Faculty of Arts and Sciences from 2024 to 2026, as Dean of Science in the Faculty of Arts and Sciences from 2018 to 2024, and as Chair of the Department of Physics from 2007 to 2010. Prior to joining Harvard, he held faculty positions at the University of California, Santa Barbara and the University of Washington. As a member of the High-Z Supernova Search Team, Dr. Stubbs shared in the discovery of the accelerating expansion of the universe, work for which he and his colleagues received the Gruber Prize in Cosmology and the Breakthrough Prize in Fundamental Physics. He also served as the inaugural project scientist of the Vera C. Rubin Observatory. Dr. Stubbs is a member of JASON, an independent group of scientists that advises the U.S. government on matters of national security. He holds a B.Sc. in physics from the University of Virginia and a Ph.D. in physics from the University of Washington.

Dr. Stubbs was selected to serve as a Trustee because of his expertise in experimental physics and the application of AI to science and education, and his experience leading scientific projects across academia, government, and the national laboratories.

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We provide funding to the LTBT, which holds all of our Class T common stock, to support its operations and the compensation of its Trustees. In the years ended December 31, 2023, 2024, and 2025, we paid $2,716,750 , $0 , and $906,089 , respectively, to the LTBT. During the six nine months ended June September 30, 2026, we paid $8,425,213 to the LTBT. and we expect to pay an additional $ between June 30, 2026 and the completion of this offering. The LTBT is accounted for as a consolidated variable interest entity ( VIE ) on our balance sheet (see Note 1 to our consolidated financial statements included elsewhere in this prospectus).

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We believe that our success depends in part on establishing a capital structure that enables our co-founders, management, and board of directors to focus on strategic initiatives that create lasting value for our stakeholders, rather than facing pressure to prioritize short-term results or purely pecuniary objectives at the expense of our long-term vision and mission. Immediately prior to the completion of this offering, we will issue a single share of Class F common stock, a special class of our common stock, to the Founder LLC, a limited liability company of which our seven co-founders will initially be the sole members and that will be managed by its members. The Our Class F common stock will be entitled to an aggregate number of votes that equals 50.1% of the total voting power of our outstanding shares of capital stock as of the applicable record date with respect to matters submitted to stockholders generally, including the election of our directors other than the Class T directors.

The Our Class F common stock will be voted by the Founder LLC in a manner determined in accordance with the Founder LLC Agreement. Generally, the Founder LLC will vote as determined by a majority of the members of the Founder LLC entitled to vote thereunder. Our seven co-founders will initially be the sole members. Upon the incapacity or death of any of our co-founders, a successor member may be admitted to the Founder LLC until the tenth anniversary of the completion of this offering. We refer to our seven co-founders and any successors in the Founder LLC as Continuing Founders.

When there have been fewer than three Continuing Founders (not including any successor member who is a Non-Qualifying Member as defined in the Founder LLC Agreement) for 90 consecutive calendar days, a 450- day transition period will commence (the Class F Transition Period ). Upon completion of the Class F Transition Period, all of the our Class F common stock and Class E common stock then issued and outstanding will be redeemed by us for no consideration and certain other governance changes will take effect.

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Founders, which may not be approved during the Class F Transition Period or if the grant of the leave of absence would itself cause the Class F Transition Period to commence.

A Continuing Founder will be removed from the Founder LLC upon the earliest to occur of (i) such Continuing Founder s resignation as a member of the Founder LLC (ii) such Continuing Founder s death or incapacity (iii) with respect to each of our seven original co-founders, such original co-founder s ceasing to hold (together with such original co-founder s related holders) on any record date for a vote of our stockholders a number of shares 13 Benjamin Mann has been an integral part of Anthropic since its founding in January 2021 and, given his role in establishing Anthropic, is often referred to as a co-founder. However, Mr. Mann is not a member of the Founder LLC nor a Continuing Founder upon the completion of this offering, and accordingly will not participate in determining how our Class F common stock is voted. Except as set forth in this paragraph, references to our co-founders elsewhere in this prospectus do not include of Class A common stock (including shares subject to options, RSUs, and other convertible securities) equal to at least 2% of the shares of Class A common stock held by such original co-founder and their related holders as of the completion of this offering (iv) such Continuing Founder s removal for cause (as defined in the Founder LLC Agreement), which includes specified competitive activities described in the Founder LLC Agreement (v) with respect to any successor member admitted to the Founder LLC prior to the commencement of the Class F Transition Period, other than a successor member who is a member during the Class F Transition Period, the tenth anniversary of the completion of this offering or (vi) with respect to each of our seven original co-founders, the commencement of a leave of absence approved by a Supermajority of the other Continuing 13 Benjamin Mann has been an integral part of Anthropic since its founding in January 2021 and, given his role in establishing Anthropic, is often referred to as a co-founder. However, Mr. Mann is Founders, which may not a member of be approved during the Founder LLC nor a Continuing Founder upon Class F Transition Period or if the completion grant of this offering, and accordingly will not participate in determining how the leave of absence would itself cause the Class F common stock is voted. Except as set forth in this paragraph, references Transition Period to our co-founders elsewhere in this prospectus do not include Mr. Mann. commence.

Each Continuing Founder will be entitled to one vote when determining how the our Class F common stock will be voted. If a majority of the Continuing Founders cannot agree on how the our Class F common stock will be voted, then the our Class F common stock will generally be voted proportionately with the votes of the our Class A common stock cast on the matter (subject to a quorum of a majority of outstanding Class A common stock). With respect to certain matters, the our Class F common stock will be voted for the proposal only if a greater threshold of Continuing Founders agree, and if the greater threshold is not met, the our Class F common stock will be voted against the proposal. See the section titled Description of Capital Stock Class F Common Stock Voting Mechanics.

The Founder LLC Agreement will not govern the voting of any shares of our Class A common stock held by the co-founders or their related holders. Each co-founder (or their related holders) will be able to vote shares of our Class A common stock held by them in their discretion, regardless of the manner in which the Founder LLC will vote the our Class F common stock.

The voting power of the our Class F common stock will not be impacted by future issuances of our capital stock that may cause economic or voting dilution to stockholders, such as issuances for capital raising purposes, acquisitions, or employee compensation. This structure will allow the Founder LLC to determine the outcome of matters submitted to a vote of our stockholders generally, including the election of those directors not elected by the LTBT, certain amendments to our organizational documents, and the approval by our stockholders of any merger, consolidation, sale of substantially all our assets, or other major corporate transaction requiring stockholder approval.

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The Our Class E common stock will not have any right to vote except on certain specified matters (or as otherwise required by law) the nomination or proposed removal of the Specified Class T Director or a change in the director designated as the Specified Class T Director (in circumstances where our NGC does not concur with the LTBT s proposed action) and certain proposals to amend the terms of the LTBT and the rights of the our Class T common stock or to redeem the our Class T common stock.

When voting upon a proposal to nominate or remove the Specified Class T Director or a change in the director designated as the Specified Class T Director (in circumstances where our NGC does not concur with the LTBT s proposed action), the requisite approval of the our Class E common stock will require a majority of votes cast by the our Class E common stock and quorum will require the presence, in person or by proxy, of a majority of the outstanding shares of Class E common stock.

When voting on a proposal to amend the terms of the LTBT or the rights of the our Class T common stock or to redeem the our Class T common stock, in addition to the requisite approval of the our Class A common stock as described more fully in the section titled Changes to the LTBT and Class T Common Stock, section above, the requisite approval of the our Class E common stock will require until the third anniversary of the completion of this offering, if the our Class F common stock is acting pursuant to the unanimous approval of the Continuing Founders, a majority of the votes cast by the our Class E common stock (subject to a quorum of 40% of the our outstanding Class E common stock) or at any time when the our Class F common stock remains outstanding, 75% of the votes cast by the our Class E common stock (subject to a quorum of a majority of outstanding Class E common stock).

Our amended and restated certificate of incorporation, which will become effective immediately prior to the completion of this offering, will authorize Class E common stock, which will be issued to our employees as follows (i) one share of Class E common stock for each six months of employment completed with us and (ii) one share of Class E common stock for each share of Class A common stock that such employee has pledged to donate through our donation matching program, or any similar program we may establish in the future. The timing for issuing the Class E common stock will be determined after the closing of this offering. Our co- founders co-founders will not receive any shares of Class E common stock, and to the extent that a holder of Class E common stock later serves as a successor to any co-founder s interest in the Founder LLC, they will not be able to vote any Class E common stock they hold during the period of such service.

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Decisions regarding our business and affairs are made by our board of directors. Immediately prior to the completion of this offering, we will enter into the Stockholders Agreement with the LTBT and the Founder LLC, under which they will agree to vote their shares and take other actions to give effect to the board composition, director nomination, and director removal provisions described in our governing documents.

Decisions regarding our business and affairs are made by our board of directors. Collectively, the LTBT and the Founder LLC will have the ability to elect all members of our board of directors. Regardless of the class or classes of stock by which a director is elected, there is no limit to the number of terms a director may serve.

Regardless of the class or classes of stock by which a director is elected, there is no limit to the number of terms a director may serve.

While the LTBT has significant influence over our board of directors through its ability to generally elect and remove a majority of the authorized members of our board of directors, neither the LTBT nor the Trustees have decision-making authority in the day-to-day management or strategy setting of the company. The LTBT s role is to select directors who are well-equipped to make decisions in furtherance of the responsible balancing of the pecuniary interests of our stockholders, the best interests of those materially affected by our conduct, and the Company Purpose, and to support our management s decision-making through advice and guidance. The Trustees aim to choose directors who have the necessary business skills, experience, and expertise to oversee the management of our business effectively and in a manner that responsibly balances (i) the pecuniary interests of our stockholders, (ii) the best interests of those materially affected by our conduct, and (iii) the Company Purpose.

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Management 18 changes

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Executive compensation 53 changes

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1 unchanged paragraph

5 unchanged paragraphs

4 unchanged paragraphs

5 unchanged paragraphs

4 unchanged paragraphs

2 unchanged paragraphs

3 unchanged paragraphs

1 unchanged paragraph

2 unchanged paragraphs

1 unchanged paragraph

1 unchanged paragraph

1 unchanged paragraph

1 unchanged paragraph

1 unchanged paragraph

and 53 more changes in the filing

Certain relationships and related person transactions 4 changes

23 unchanged paragraphs

1 unchanged paragraph

7 unchanged paragraphs

16 unchanged paragraphs

and 4 more changes in the filing

Principal stockholders 26 changes

1 unchanged paragraph

3 unchanged paragraphs

1 unchanged paragraph

1 unchanged paragraph

2 unchanged paragraphs

2 unchanged paragraphs

and 26 more changes in the filing

Description of the securities 86 changes

1 unchanged paragraph

1 unchanged paragraph

2 unchanged paragraphs

6 unchanged paragraphs

9 unchanged paragraphs

3 unchanged paragraphs

3 unchanged paragraphs

2 unchanged paragraphs

3 unchanged paragraphs

2 unchanged paragraphs

5 unchanged paragraphs

103 unchanged paragraphs

6 unchanged paragraphs

3 unchanged paragraphs

4 unchanged paragraphs

5 unchanged paragraphs

9 unchanged paragraphs

2 unchanged paragraphs

1 unchanged paragraph

3 unchanged paragraphs

1 unchanged paragraph

9 unchanged paragraphs

4 unchanged paragraphs

1 unchanged paragraph

2 unchanged paragraphs

3 unchanged paragraphs

1 unchanged paragraph

1 unchanged paragraph

3 unchanged paragraphs

2 unchanged paragraphs

1 unchanged paragraph

1 unchanged paragraph

1 unchanged paragraph

7 unchanged paragraphs

2 unchanged paragraphs

5 unchanged paragraphs

and 86 more changes in the filing

Shares eligible for future sale 89 changes

1 unchanged paragraph

2 unchanged paragraphs

8 unchanged paragraphs

and 89 more changes in the filing

Plan of distribution 43 changes

2 unchanged paragraphs

5 unchanged paragraphs

2 unchanged paragraphs

3 unchanged paragraphs

5 unchanged paragraphs

8 unchanged paragraphs

23 unchanged paragraphs

11 unchanged paragraphs

and 43 more changes in the filing

Change in independent accountant 1 change

4 unchanged paragraphs

1 unchanged paragraph

and 1 more change in the filing

Notes to the financial statements 9 changes

5 unchanged paragraphs

13 unchanged paragraphs

1 unchanged paragraph

4 unchanged paragraphs

13 unchanged paragraphs

38 unchanged paragraphs

5 unchanged paragraphs

and 9 more changes in the filing

Note 1: Description of Business and Summary of Significant Accounting Policies 1 change

7 unchanged paragraphs

1 unchanged paragraph

and 1 more change in the filing

Note 2: Revenue 1 change

and 1 more change in the filing

Note 8: Supplemental Financial Information 2 changes

1 unchanged paragraph

2 unchanged paragraphs

and 2 more changes in the filing

Note 12: Net Loss per Share 1 change

2 unchanged paragraphs

and 1 more change in the filing

Note 13: Commitments and Contingencies 3 changes

3 unchanged paragraphs

and 3 more changes in the filing

Note 14: Segment and Geographical Information 1 change

2 unchanged paragraphs

and 1 more change in the filing

Note 15: Business Combinations 2 changes

5 unchanged paragraphs

and 2 more changes in the filing

Note 16: Subsequent Events 2 changes

5 unchanged paragraphs

and 2 more changes in the filing

Note 17: Subsequent Events (Unaudited) 3 changes

1 unchanged paragraph

1 unchanged paragraph

and 3 more changes in the filing

Recent Sales of Unregistered Securities 9 changes

8 unchanged paragraphs

1 unchanged paragraph

1 unchanged paragraph

and 9 more changes in the filing

Exhibits 6 changes

15 unchanged paragraphs

1 unchanged paragraph

17 unchanged paragraphs

3 unchanged paragraphs

10 unchanged paragraphs

and 6 more changes in the filing