Can Anthropic Single-handedly Save the Entire AI Industry Chain?
SemiAnalysis recently reported that Anthropic is projected to achieve $1 billion in GAAP EBITDA by the third quarter of 2026, translating to a profit margin of approximately 6%. Meanwhile, its Annual Recurring Revenue (ARR) has surged from $9 billion at the end of 2025 to over $60 billion currently. If Anthropic maintains a monthly Net New ARR (NNARR) pace of around $15 billion, its ARR could reach $300 billion by the end of 2027. This would correspond to a $6 trillion enterprise value, making it the most valuable company in the world, according to SemiAnalysis.
Anthropic confidentially filed for an IPO on June 1st. Its superior financial metrics and business model suggest it should go public before OpenAI to seize the initiative in the competition for capital.
What's driving the ARR surge?
Anthropic's revenue performance stems from the explosive adoption of Claude Code. Data shows that Claude Code currently accounts for over 7% of all code commits on GitHub, directly propelling the company's monthly new ARR from $3 billion in January to $11 billion in March.
In terms of revenue structure, Anthropic and OpenAI show a stark divergence. Approximately 75% to 85% of Anthropic's ARR comes from usage-based API business, with consumer subscriptions accounting for only 5% of total ARR. In contrast, in Q1 2026, over 65% of OpenAI's revenue still came from subscription models, with consumer ARR making up about 40%.
The core advantage of the API model is the absence of a revenue cap per user. As existing customers adopt more agentic workflows, their token consumption and corresponding revenue continue to grow, enabling expansion without the need to acquire new customers. Anthropic's CFO disclosed in a podcast this May that the company's Net Revenue Retention (NRR) stands at a staggering 500%. Among customers contributing $30 billion in ARR in Q1, this same cohort contributed only $2 billion a year ago.
Significant gross margin improvement
Differences in business models are directly reflected in gross margins. SemiAnalysis estimates that Anthropic's current blended gross margin has risen to the mid-60% range, up from negative 94% in 2024. Notably, its API business boasts a gross margin exceeding 80%.
The primary driver behind this massive margin expansion is improved inference efficiency. Measured by ARR per megawatt of compute, Anthropic is on track to reach $60 million later this year, up from just $16 million nine months ago. Since inference compute costs are largely fixed, marginal profit margins approach 100% when the volume of tokens processed per unit of compute or token pricing increases.
If both Anthropic and OpenAI reach $1 trillion in ARR, OpenAI's gross profit would be roughly $25 billion lower than Anthropic's, as it needs to support over 900 million free users (estimated to cost about $0.70 per person per month). This gap will directly impact the companies' ability to reinvest in training next-generation models.
Which stocks will benefit?
Anthropic's surging ARR and rising compute demand will broadly benefit chipmakers, including $NVIDIA (NVDA.US)$, $Advanced Micro Devices (AMD.US)$, $Broadcom (AVGO.US)$ and $Marvell Technology (MRVL.US)$ . Beyond that, other key beneficiaries include:
1. Cloud service providers will be among the biggest winners. On the distribution front, the "Token-as-a-Service" (TaaS) model—sold indirectly through hyperscale cloud platforms like $Amazon (AMZN.US)$ AWS Bedrock and $Microsoft (MSFT.US)$ Azure Foundry—is growing rapidly. It now accounts for 15% to 20% of Anthropic's ARR, up from just 5% to 10% a quarter ago. Paying hyperscalers a 20% to 30% revenue share remains economically justified given the enterprise customer reach and compliance convenience they provide. In addition, Anthtopic has signed a computing power agreement with $SpaceX (SPCX.US)$ 's xAI and is also in talks with $Meta Platforms (META.US)$ .
2. Workflow Management: Once AI automatically generates code, the frequency of project iterations, code commits, and bug troubleshooting increases, driving growth in paid subscriptions for R&D management and code hosting. Key companies include $Atlassian (TEAM.US)$ , $DigitalOcean (DOCN.US)$ , and $JFrog (FROG.US)$ . Notably, DigitalOcean is up over 250% this year.
3. Data SaaS: The mass production of applications leads to surge in data storage, computing, and runtime monitoring usage. The industry standard is pay-as-you-go billing. Relevant companies include $Datadog (DDOG.US)$ , $MongoDB (MDB.US)$ , and $Snowflake (SNOW.US)$ .
4. CDN (Content Delivery Network) Companies: After AI generates applications with a single click, developers deploy them to nearby edge nodes. Cloudflare Workers and Akamai Edge Cloud handle lightweight AI application hosting and local inference. AI code previews and online debugging require proximate computing power, upgrading CDNs from pure traffic distribution to edge AI computing platforms and opening up new avenues for value-added payments. The companies involved include $Cloudflare (NET.US)$, $Akamai (AKAM.US)$ , and $Fastly (FSLY.US)$ .
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