Anthropic Could Beat OpenAI to Wall Street by Over a Year

Anthropic is reportedly preparing an IPO prospectus after 2025 revenue surged 1,050% year over year to $4.6 billion, potentially positioning it to list ahead of OpenAI. The company posted an $8.06 billion operating loss and spent $7.33 billion, or 58% of operating expenses, on AI infrastructure and cloud compute, while projecting $518 billion of future infrastructure and computing expenditures. Both Anthropic and OpenAI are targeting potential valuations of up to $2 trillion; OpenAI raised $122 billion at an $852 billion valuation in March, giving it greater flexibility to defer an IPO until its planned 2027 timeline.

Analysis

The investable read-through is less about a prospective listing and more about whether frontier-lab compute commitments convert into durable cloud revenue rather than low-return, balance-sheet-intensive capacity. AMZN and GOOG can monetize both infrastructure consumption and higher-value managed AI services, but incremental capex may outrun revenue recognition for several quarters; the market will focus on cloud segment operating-margin progression and disclosed customer concentration. A lab funding cycle also increases bargaining power for hyperscalers that control scarce power, networking, and accelerator supply.

NVDA remains a volume beneficiary only if the spending is accelerator-led rather than increasingly routed through hyperscaler-designed silicon such as Google TPUs and Amazon Trainium. That distinction matters: cloud compute spending can be strongly positive for AMZN/GOOG while delivering a weaker-than-expected incremental GPU revenue signal for NVDA. Watch hyperscaler capex guidance, lead times, and AI-cloud revenue commentary over the next two earnings cycles rather than extrapolating headline infrastructure figures.

A public-market valuation near mega-cap levels would require investors to underwrite many years of exceptional growth despite negative operating leverage and likely recurrent external financing. The contrarian view is that an IPO could de-risk private-market liquidity but simultaneously impose a public valuation discipline that pressures comparable AI multiples; a weak debut would be more damaging to AI software and infrastructure sentiment than to diversified hyperscalers. The claimed future spend should be treated as an aspiration until contracts, power procurement, and financing terms are independently verified.

Key Decisions for Investors

• Maintain a 1-3 month tactical long AMZN versus GOOG only if AWS reports accelerating AI revenue with stable or improving segment margin; use a 5% relative stop because the thesis fails if AI demand requires disproportionate AWS capex without monetization.
• Do not add directional NVDA exposure solely on this signal. Set an alert around next-quarter hyperscaler capex and custom-silicon disclosures: add only if aggregate capex rises while management commentary confirms GPU-based capacity expansion rather than substitution toward internal accelerators.
• For 6-18 months, favor a basket long AMZN and GOOG over high-multiple, unprofitable AI application software via IGV as a hedge: infrastructure providers retain pricing power if model vendors consolidate or face funding constraints. Exit if cloud operating margins decline for two consecutive reported quarters despite AI revenue growth.
• Avoid attempting to position around a prospective frontier-lab IPO until a filed prospectus provides contracted compute obligations, revenue concentration, gross-margin trajectory, and financing covenants. A valuation implying an extreme forward-revenue multiple would create a potential post-lockup short watchlist, not an automatic long.