Just six months ago, Anthropic, which was far behind, has now left OpenAI far behind.
On May 26, according to The Information’s report, Anthropic’s annualized revenue has reached nearly $45 billion, while OpenAI’s annualized revenue has just exceeded $30 billion, currently estimated to be around $33 billion. This means that Anthropic’s revenue is at least 35% higher than OpenAI’s. This number was almost unimaginable six months ago. By the end of 2025, Anthropic’s annualized revenue was only $9 billion, less than half of OpenAI’s.
In the first five months of this year, Anthropic’s revenue has grown by about 5 times. In the same period, OpenAI’s revenue growth exceeded 50%—impressive in any industry, but quite modest compared to Anthropic. A source familiar with the matter told The Information that although OpenAI’s annualized revenue has exceeded $30 billion, it is currently “not much higher.”
The two companies have different business models: OpenAI’s revenue mainly comes from ChatGPT subscriptions, while Anthropic mainly relies on selling AI programming and other white-collar work scenario API access to enterprises. However, they still compete directly in their respective markets, and public market investors will inevitably compare the two.
Revenue is just one aspect. What is more crucial is profitability. Anthropic is expected to achieve around $559 million in operating profit in the second quarter, with an operating profit margin of about 5%.
OpenAI’s situation is quite the opposite. OpenAI’s first-quarter operating loss rate was as high as 122%—this is even after excluding major items such as equity incentives. In other terms, the operating loss for that quarter was at least $7 billion. OpenAI’s earlier predictions for this year show that it will burn about $25 billion in cash for the whole year, with AI server rental costs as high as $32 billion. Additionally, OpenAI also needs to give 20% of total revenue to Microsoft, an agreement that will continue until 2030. If this year’s revenue reaches the previously predicted $30 billion, this share will amount to approximately $6 billion.
Anthropic also needs to share revenue with cloud partners, but Anthropic’s revenue calculation includes the total amount sold through other cloud service providers, part of which will eventually be returned to these partners. It is worth noting that Anthropic’s current profitability status is not without risks. With rapidly growing revenue, Anthropic needs to significantly expand server resources, which may put it back into a loss-making position.
This reversal of revenue and profitability is directly affecting the IPO timelines of the two companies. Reports indicate that OpenAI’s CFO Sarah Friar had previously expressed concerns to CEO Sam Altman about rushing the IPO plans. However, the situation is now different—faced with the stronger financial position of Anthropic, OpenAI’s rush to go public has instead become a “financially prudent choice.”
The logic is simple: if Anthropic submits its IPO application first and successfully goes public, the public market investors will directly compare the financial data of the two companies. At that time, with faster revenue growth and realized profitability, Anthropic will have a clear advantage in the valuation narrative. At the current growth rate, Anthropic is expected to surpass the revenue scale of mature tech companies like Netflix, SAP, and Salesforce within the next year.
[BlockBeats]
Anthropic’s Revenue Surge Reshapes AI Landscape & Creates Opportunities for Blockchain Convergence
The recent revelation that Anthropic has surpassed OpenAI in annualized revenue by at least 35%—reaching approximately $45 billion compared to OpenAI’s $33 billion—represents a seismic shift in the artificial intelligence landscape. This dramatic reversal, with Anthropic’s revenue growing fivefold in just five months while OpenAI’s growth appears modest in comparison, carries significant implications for the blockchain and crypto market, particularly for projects positioned at the intersection of AI and decentralized technologies.
Market Impact and Token Price Considerations
While this development doesn’t directly impact major cryptocurrencies like Bitcoin or Ethereum, it creates ripple effects across the AI-focused segment of the crypto ecosystem. We could see:
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Increased attention on AI tokens: Projects like Fetch.ai (FET), SingularityNET (AGI), Ocean Protocol (OCEAN), and Bittensor (TAO) may experience heightened interest as investors seek exposure to the AI growth story through blockchain-based proxies.
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Selective performance divergence: Not all AI blockchain projects will benefit equally. Those with demonstrable utility in enterprise AI workflows, data markets, or decentralized computing infrastructure are more likely to outperform.
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Valuation realignment: The market may reassess the value proposition of blockchain AI projects relative to their centralized counterparts. Projects that can articulate clear advantages in data privacy, verifiability, or decentralized governance may command premium valuations.
Risks in the Current Landscape
The dominance of centralized AI players like Anthropic introduces several risks for blockchain-based AI initiatives:
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Centralization risk: As Anthropic and OpenAI consolidate market power, they could potentially incorporate blockchain features internally, reducing the need for external decentralized solutions.
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Resource competition: The article highlights astronomical compute costs—OpenAI projecting $32 billion in server rental costs this year. This creates a barrier to entry for decentralized alternatives that must compete with economies of scale.
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Regulatory arbitrage: As AI becomes increasingly concentrated in the hands of a few large companies, regulators may impose stricter controls. Blockchain AI projects could face regulatory uncertainty at the intersection of these two complex technological domains.
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Investment diversion: The spectacular growth and profitability of AI companies like Anthropic could divert capital away from blockchain AI projects, even when they offer complementary value propositions.
Strategic Opportunities for Blockchain Projects
Despite these risks, the AI market’s rapid expansion creates compelling opportunities for blockchain solutions:
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Data privacy and monetization: Anthropic’s enterprise focus on “white-collar work scenario API access” suggests significant demand for secure, private AI solutions. Blockchain-based data markets like Ocean Protocol could facilitate more transparent data monetization while preserving privacy.
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Decentralized compute resources: The staggering compute costs mentioned in the article highlight the inefficiency of centralized AI infrastructure. Projects that can incentivize distributed computing resources through token mechanisms could capture significant value.
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Verifiable AI provenance: As AI models become more powerful, the ability to verify their training data, decision-making processes, and potential biases becomes critical. Blockchain solutions for AI transparency and accountability could fill this growing need.
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Complementary business models: Rather than competing directly with ChatGPT-style applications, blockchain AI projects can focus on infrastructure, data marketplaces, or specialized AI tools that serve as complementary layers to the centralized AI ecosystem.
Investment Implications for Crypto Investors
For experienced crypto investors, this development reinforces several strategic considerations:
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Differentiate between AI hype and real utility: Not all projects claiming AI integration will benefit from the broader AI market’s growth. Focus on those with clear technical advantages and sustainable tokenomics.
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Enterprise adoption as a key indicator: Anthropic’s success highlights the importance of enterprise use cases. Blockchain AI projects with demonstrated enterprise traction may outperform those focused solely on consumer applications.
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Monitor regulatory developments: As AI becomes more concentrated, regulatory frameworks will evolve. Projects that proactively address compliance concerns may have a competitive advantage.
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Long-term thesis on decentralization: The most valuable blockchain AI projects will likely be those that solve fundamental problems created by AI centralization—whether through enhanced privacy, better incentives for data sharing, or more equitable access to AI capabilities.
Conclusion
Anthropic’s remarkable revenue growth and profitability demonstrate that sustainable business models are emerging in the AI space. While this creates challenges for blockchain-based alternatives, it also illuminates specific pain points that decentralized technologies can address. The most promising investment opportunities will likely be found in blockchain AI projects that complement rather than compete with centralized AI leaders, focusing on areas where decentralization provides clear advantages in privacy, security, or economic incentives.
As we approach what could be a landmark year for both AI and blockchain IPOs, investors should carefully evaluate how blockchain AI projects position themselves within the evolving technological landscape. Those that can articulate a clear value proposition relative to the emerging centralized AI giants may offer the most compelling risk-adjusted returns in the coming years.