Intelligence Per Dollar | Tomasz Tunguz

Tomasz Tunguz<br>Venture Capitalist at Theory Ventures

Yesterday Microsoft added a new metric to a model release card, one that will likely become a standard.1

Average token usage.

In the first row, the Microsoft model hits 71.6 on SWE-Bench Verified using about a third of the tokens Claude Haiku 4.5 burns.

Benchmarks are now measured on two different dimensions, the overall performance & the cost to achieve that intelligence.

This is yet another sign that the era of subsidies2, tokenmaxxing3, & all-out performance for many use cases is over.

Even the most valuable companies in the world cannot afford state-of-the-art intelligence for every conceivable use case.4 Uber capped employee AI spending after blowing through its budget in four months.5 Salesforce is spending $300M on Anthropic tokens & has frozen engineering hires.6

This new dual benchmark answers the buyer&rsquo;s only question : what is my intelligence per dollar?

Artificial Analysis already benchmarks this.7 GPT 5.5 & Claude Opus 4.8 land within a point of each other on the Intelligence Index, around 60. Running the index costs $3,357 on GPT 5.5 & $4,685 on Opus 4.8. Same answer, 40% more expensive.

Model companies must now compete on both dimensions. The application layer will compete one level up, on dollars per outcome, what a closed ticket, a shipped PR, or a resolved support case actually costs.

Every layer in the stack now has to price the same way the customer thinks : per result, not per token.

Introducing MAI-Code-1-Flash — Microsoft announces a new coding model with average token usage on the release card. ↩︎

The Unsustainable Subsidy — The era of AI subsidies is ending. ↩︎

Tokenmaxxing — Models that game benchmarks with extra tokens are losing their edge. ↩︎

Microsoft cancels Claude Code licenses, shifting developers to GitHub Copilot CLI — Microsoft cancelled Claude Code licenses across its Experiences and Devices division (Windows, Microsoft 365, Outlook, Teams, Surface) after engineering usage outran budgets. ↩︎

Uber caps employee AI spending after blowing through budget in 4 months — Uber caps employee AI spending after blowing through budget in four months. ↩︎

Salesforce Spends $300M on AI, Freezes Engineering Hires — Salesforce Spends $300M on AI, Freezes Engineering Hires. ↩︎

AI Model & API Providers Analysis — Independent analysis of AI model costs. ↩︎

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GP at Theory Ventures. Former Google PM. Sharing data-driven insights on AI, web3, & venture capital.

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