The global competitive landscape for cutting-edge artificial intelligence is undergoing a profound transformation.
A new report from research firm SemiAnalysis indicates that, following a year of aggressive capital investment and structural reorganization, Meta's Meta Superintelligence (MSL) division is positioned to overtake Google in advanced AI capability rankings within the next six months.
Concurrently, Anthropic has established a dual lead in profitability and growth rate, driven by the explosive growth of its Claude Code product in the enterprise market, and confidentially filed for an IPO in June. The power dynamics of the AI industry are evolving from a two-horse race between Google and OpenAI towards a new tripartite order involving Meta Platforms, Inc. (META), OpenAI, and Anthropic.
These developments have triggered an immediate market reaction. Meta Platforms, Inc. (META) shares rose approximately 4% on the day, while Alphabet (GOOGL) shares fell about 1%, reflecting growing market concern over Google's standing in the AI race. Adding another variable to the competitive discussion, Elon Musk publicly stated on social platform X that Anthropic is "obviously" the current frontrunner in the AI field.
An earlier financial deep-dive on Anthropic's IPO by SemiAnalysis projected the company would achieve over $10 billion in GAAP EBIT profit by Q3 2026, while OpenAI's EBIT margin remains at negative 100%. Based on this, SemiAnalysis assigns Anthropic a benchmark valuation of $6 trillion and suggests it should complete its public listing ahead of OpenAI to use its capital advantage to further solidify its lead in frontier models.
Meta's Three-Pronged Advance: Compute, Data, and Talent
The core thesis of the SemiAnalysis report is that the pace of Meta's expansion in computing scale will allow it to surpass the combined AI compute capacity of OpenAI and Anthropic by year-end.
According to a Reuters report citing an internal memo, Meta plans to invest up to $145 billion in AI infrastructure this year, deploy 7 gigawatts of compute in 2026, and double that figure to 14 gigawatts by 2027. Supporting this ambition is the simultaneous construction of five gigawatt-scale "titan" hyperscale data center clusters and a proprietary "AI-Backbone" network architecture, which allows Meta to asynchronously scale complex training tasks across thousands of kilometers.
On the chip front, Reuters reported that Meta will begin mass production of its internally developed "Iris" AI chip in September. Co-designed with Broadcom (AVGO) and manufactured by TSMC, the chip completed vulnerability testing in just six weeks and has secured multi-year supply agreements with Samsung, SanDisk, and Sumitomo Electric.
Regarding data and talent, Meta has reassigned 3,000 engineers to an internal reinforcement learning (RL) environment factory, building proprietary data pipelines that commercial vendors cannot replicate. Furthermore, Meta invested $14.3 billion in Scale AI, leveraging this to poach top researchers en masse from organizations like OpenAI and Anthropic.
SemiAnalysis argues that evaluating MSL's current benchmark performance is "missing the forest for the trees," and that the crucial factor is "the slope, not the intercept." The report suggests that if Mark Zuckerberg maintains the current level of capital investment, Google risks being permanently excluded from the top tier of global AI hyperscalers.
Anthropic: B2B Profitability Model Establishes a Lead
If Meta's advantage lies in compute and infrastructure, Anthropic's moat is built on its business model and financial quality.
SemiAnalysis data shows that Claude Code now accounts for over 7% of all code commits on GitHub. This product drove Anthropic's Annual Recurring Revenue (ARR) from $9 billion at the end of 2025 to a single-quarter jump of $30 billion in January, $70 billion in February, and $110 billion in March, reaching an estimated $30 billion for Q1 2026. To date, Anthropic's ARR exceeds $60 billion, with net new ARR scaling to over $10 billion per month.
Anthropic's financial structure contrasts sharply with OpenAI's. Approximately 75% to 85% of Anthropic's revenue comes from usage-based API business, whereas OpenAI still derived over 65% of its Q1 2026 revenue from subscription models, with consumer subscriptions accounting for about 40% of that. SemiAnalysis estimates OpenAI must service over 900 million free users at a cost of roughly $0.70 per user per month, dragging down its overall gross margin by 20% to 30%.
On profitability, SemiAnalysis projects Anthropic will achieve over $10 billion in GAAP EBIT (a margin of about 6%) by Q3 2026, while OpenAI's EBIT margin remains negative 100%. Anthropic's CFO Krishna Rao previously disclosed a Net Dollar Retention (NDR) rate of 500%, meaning customers who contributed $2 billion in ARR a year ago now contribute $12 billion. SemiAnalysis extrapolates that if Anthropic can accelerate its monthly net new ARR to $15 billion, its ARR could reach $300 billion by the end of 2027, corresponding to an enterprise value of $6 trillion.
Google: From Frontrunner to the Chased
In this three-way contest, Google's position is the most delicate.
SemiAnalysis states bluntly in its report that Google has "fallen significantly behind" in the frontier AI race and predicts Meta will surpass it within six months. Elon Musk's designation of Anthropic as the obvious current leader also notably omits Google from the top-tier discussion.
The SemiAnalysis analytical framework suggests the decisive variables in frontier AI competition have shifted from pure model capability to a combination of computing scale, business model, and capital access.
On these three dimensions, Meta is catching up rapidly, Anthropic has established a lead, and Google faces pressure from being squeezed from both sides.
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