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NewsMaterial3 min readDisconfirmAI Editorial

OpenRouter Head of Insights Peter Walker: AI Inference Is Now a Commodity; Enterprises Should Procure Based on Landed Cost

Data from the OpenRouter platform shows that token usage has grown approximately 300-fold over two years while unit prices have dropped by 80%, decoupling volume from expenditure. Peter Walker, Head of Insights at OpenRouter, argues that AI inference exhibits all the characteristics of a commodity market—falling unit costs, rising volume, and frequent shifts in optimal suppliers. Consequently, enterprises should no longer procure AI services via software subscription models but instead make per-request decisions based on landed cost, which comprehensively factors in caching discounts, wait times, and retry costs.

2026-10-22 19:35 GMT+8

In January 2025, OpenRouter processed approximately 500 billion tokens per week; by late September 2026, this figure had risen to 164 trillion. Over the same period, the average price paid per million tokens fell from $0.77 to $0.14. In an article published on OnlyCFO, Peter Walker, Head of Insights at OpenRouter, pointed out that the simultaneous surge in usage and precipitous drop in unit prices are characteristic features of a commodity market, not a software market. Most enterprises still procure AI as if it were software: selecting a vendor, negotiating annual commitments, and re-evaluating at fixed intervals. Walker argues that this logic is now obsolete.

The decoupling mechanism operates on three levels. First, open-weight models now account for approximately 60% of weekly token volume on OpenRouter but only 26% of expenditure—the bulk of routine tasks such as classification, extraction, coding subtasks, and agent steps has migrated to models costing only a fraction of frontier models. Second, on February 6, 2026, software agents surpassed human users as the primary source of tokens; by late September, agent workloads accounted for approximately 131 trillion tokens per week, compared to about 18 trillion from human users. Agents resend the same long context at every step, making prompt caching the most critical pricing feature in AI—cached tokens are billed at a tiny fraction of the normal price. The cache rate for agent traffic on newly released models this quarter has reached 88%, whereas models released in spring 2025 saw only 55%. Third, frontier labs OpenAI and Anthropic have both recently released highly capable models with significantly lower prices, further driving down the average price.

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The practical implication for procurement is that approximately 77% of requests on OpenRouter are routed to models served by multiple providers, meaning most traffic involves per-request supplier decisions. OpenRouter’s upgraded routing algorithm no longer looks solely at the input token unit price but prices each request according to what Walker calls landed cost: the effective price after caching discounts plus wait cost plus retry cost. A request costing $1.00 with an 80% success rate actually costs $1.25 per successful answer. For three popular open-weight models, the actual price paid by customers was 43% to 89% lower than the list price, and the provider with the lowest list price was often not the cheapest in practice. Walker’s conclusion is that this market moves by the minute, not by the quarter.

Walker advises CFOs to manage AI as a volatile input within their enterprise models. Increased usage does not equate to increased expenditure—hundreds of companies on OpenRouter have successfully reduced spending even as token usage rose significantly. Open-weight models are not monolithic; there are substantial differences in speed, quality, and reliability when the same model is served by different providers. The most promising model may not have been launched yet—the lab ranked first by token volume on OpenRouter changed five times over eight quarters, with its leading share dropping from approximately 40% to 21%. Only companies with a culture of experimentation and a matching financial perspective can maintain their position at the frontier of applied intelligence.

It must be emphasized that all the above data come from traffic observations on the single OpenRouter platform, reflecting requests routed through that gateway; they cannot be directly equated with the AI expenditure structure of enterprises connecting directly via cloud service provider APIs or deploying locally. Walker himself noted that the article does not constitute legal, tax, or investment advice.

Sources

  • onlycfo.io↗
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