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SemiAnalysis

Engrams Embedding Entendre: Codesign for Efficient DRAM/SSD Offloading Everyone Says Datacenter Moratoriums Are Killing the US Buildout. We Mapped All 300 of Them Rubin NVL72 Agentic Inference: 67x better Performance per Dollar Where Does a Robot Think — On-Device vs Datacenter Inference Long Live the Short King: Why 4-hi HBM Wins Nvidia’s Backstop Universe – Heads I Win, Tails Who Loses? What is So Hard About Behind-The-Meter Power For Datacenters? Part 1 Where Does a Robot Think – On-Device vs Datacenter Inference – On-Device vs Datacenter Inference TPU Inference Externalization Full Steam Ahead - InferenceX Korea’s Trillion-Dollar Sovereign AI Investment: Nvidia Wins, Hynix Loses Most Neoclouds Suck At Security OpenAI’ Jalapeño: Better Than Nvidia Blackwell AgentX - InferenceXv3: Does CUDA Moat Hold up in Agentic Inferencing? Are Open Models Catching Up? Cerebras's Next Generation CS-4: Fast Just Got Faster Full of Cold Air - PJM's $12B modeling mistake Ultra-High Interactivity on NVIDIA GPUs? - TileRT InferenceX SpaceX 10GW in 2027 – Why It’s Real, Will Drive $500B ARR for SpaceX, and Why Microsoft Will Be the Largest Offtaker Gemini is Cooked but GCP is Cooking Kimi K3: The Manos, The Mythos, The Legendos The Wild Wild West Of LEGO Datacenters Can AMD break the CUDA Moat? AMD Advancing AI 2026 Vera Rubin NVL72 vs GB200 NVL72? Inference TCO & Architecture Analysis Meta’s Infrastructure Team Needs A Culture Reset The Future of Meta Superintelligence: A 1 Year Progress Update Nvidia GPU Debt Backstop Unleashes the AI Project Trinity: Capital, Offtake and Datacenters Meta Compute: Everyone Wants To Be A Neocloud EMIB-T, HBM4 Challenges, Microfluidic Cooling, Photonic Interconnects TokenBudgeting: Our Conversations with Enterprises on Token Spend US Grid Constraints: Towards 40GW+ of Behind-The-Meter Datacenter by 2028?
Anthropic 3Q26 Profit Over $1B: The Anthropic IPO Financi...
Joey Brookhart · 2026-07-08 · via SemiAnalysis

When Dario Amodei left OpenAI to start Anthropic in early 2021, the viral release of ChatGPT was over 18 months away and the commercialization of LLMs was practically zero. Just a few short years later, Anthropic and OpenAI combine for ~$100B of ARR and a clear winner emerged in the profitable monetization of AI models in 2026 as Claude Code took the software development world by storm.

Anthropic confidentially filed for IPO on June 1st. Over 1 month later, equity raises from hyperscalers loom, and a reported OpenAI push out of their own IPO until 2027 has led some to question the ability of the labs to raise. However, Anthropic is the clear clubhouse leader in capturing the B2B market today and is doing so in a profitable manner against an unfocused and money-burning competitor.

With this lead, we expect Anthropic to take advantage of their superior business model and margins to invest in further in new models that help extend their lead and monetization over closed and open source competitors. Anthropic has the ability to truly make OpenAI dance and we see Anthropic as the first $6T company as a base-case possibility if they continue to execute. Pricing power, gross margins, business model, and profitability are all reasons for Anthropic to IPO first and put the impetus on OpenAI to open their financials and raise the necessary capital to compete and fund the massive AI buildout still to come.

We’ve already seen 2 AI Labs IPO this year (Zhipu and Minimax from China), but Anthropic would be the first AI lab of this scale to do so. A confidential filing means there are no public numbers disclosed. Fortunately, the Tokenomics team at SemiAnalysis works to build the financials from the bottom-up by SKU, tier, and customer type. Recently, a WSJ article on Anthropic’s financials confirmed the accuracy of the work our Tokenomics team does across labs and hyperscalers to help investors, corporates, and other stakeholders understand the economics and financials of the AI Ecosystem.

In this article, we’ll dive deep into the work our team has done in the Tokenomics Model and walk you through the financial details of Anthropic, how that compares to OpenAI, where we see the market moving, and implications for the value chain and broader AI market. While other SemiAnalysis work focuses on the technical aspects of AI Labs, this piece will focus solely on the current and future financials, margin economics, and long-term outlook for Anthropic.