Venture capitalist Vivek Gopalan stated that companies with the worst final margins and those paying cutting-edge model prices often spend the least time on evaluations.

He described the internal practices of Anthropic and OpenAI: automating the strongest internal models at the time; once the process is established, using Opus or Fable to generate evaluations based on their own trajectories, then migrating down the intelligence hierarchy until they can no longer pass. Most large companies spend innovation budgets on pilot projects without monitoring unit costs, making the cutting-edge premium invisible, but it will soon be apparent to most.

He anticipates that evaluation coverage—the proportion of token spending on real evaluations, analogous to test coverage—will appear in due diligence, closely following gross margins, especially for AI-native companies where inference constitutes a significant portion of sales costs. Two companies with the same revenue and using the same batch of models can have vastly different gross margins, with the gap mostly stemming from evaluation coverage and the synthetic environments generated by evaluations.

The feedback loop will also move upwards: each generation of new cutting-edge models first rewrites the standard answers at the top of the hierarchy, as the evaluation limits generated by the previous generation's trajectories represent the quality of that generation; then the entire line migrates downwards, with the thresholds typically higher than last time, as cheaper models have also improved. Third-party services like ValsAI have ranked models based on task costs and accuracy, placing capability, latency, and unit price on the same table.

If internal automation remains stuck on the most expensive models, unit economics will be obscured by innovation categories. Coverage turns "can we use cheaper models to accomplish the same work" into an auditable number.

In market mechanisms, this is a shift in cost accounting rules, not model releases. Buyers need to see the investment and financial officers who understand inference costs; sellers are tool companies selling evaluation platforms and synthetic environments. Funding shifts from indiscriminate cutting-edge calls to layered routing. Beneficiaries are operational teams that can use evaluations to push traffic to lower-priced models, while pressured are innovation departments that run all pilots on the most expensive interfaces. A single post does not change the price list but will change what is asked in the next round of financing.

Source: Public Information