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The WSJ draft says Anthropic lost $80.7 billion in H1 2026, but $72 billion came from accounting charges on convertible notes, not cash. The real risks are $750 billion in planned compute spend and two customers producing one-fifth of revenue.
OpenAI and Anthropic are presenting a version of profitability that excludes their largest expenses: model training and inference. Critics compare this to an airline ignoring the cost of its jets. This financial engineering aims to create a positive outlook for potential IPOs but masks their true cash burn rate.
Traditional accounting metrics misrepresent the financial health of AI companies. Their largest expenditure, acquiring compute power, should be viewed as an investment in a valuable, appreciating asset, not as a typical operating expense. This reframes the narrative around their massive cash burn.
Reports of OpenAI's massive financial 'losses' can be misleading. A significant portion is likely capital expenditure for computing infrastructure, an investment in assets. This reflects a long-term build-out rather than a fundamentally unprofitable operating model.
Despite an $8 billion operating loss, investors are targeting a historic valuation for Anthropic's IPO. This shows a market shift where exponential growth projections for leading AI companies are deemed far more important than current profitability metrics, treating them differently from pre-AI era companies.
Anthropic's leaked 2025 financials reveal a staggering burn rate. Despite $4.6 billion in revenue, the company spent $12.65 billion, resulting in an $8 billion operating loss. This highlights the massive capital requirements and current unprofitability in the competitive AI sector, fueling bubble concerns.
Anthropic has committed to $518 billion in compute spend, with 80% being non-cancellable. Meanwhile, its largest customers, accounting for a quarter of revenue, are not locked into long-term contracts. This mismatch between fixed costs and variable revenue creates a significant financial risk.
When evaluating a hypergrowth company like Anthropic, the market will likely ignore massive off-balance-sheet compute commitments and unprecedented stock-based compensation (SBC). These negative financial indicators are deemed irrelevant as long as top-line revenue growth is explosive. The free pass is revoked the moment growth slows.
Despite a $380 billion valuation, Anthropic's CEO admits that a single year of overinvesting in compute could lead to bankruptcy. This capital-intensive fragility is a significant, underpriced risk not present in traditional software giants at a similar scale.
Anthropic's claims of positive operating income are based on adjusted figures that strip out major expenses like stock-based compensation and model training. This accounting practice masks the company's true financial health, which will be revealed for the first time in unadjusted IPO documents, posing a potential risk for investors.
Financial documents reveal that both OpenAI and Anthropic face an "arms race" of soaring compute costs, with OpenAI expecting to burn $85 billion in 2028 alone. This immense cash burn is their Achilles' heel, pushing them toward potentially record-breaking IPOs to fund future model development despite unsustainable losses.