LLM Token Expenditure Index: average cost per million tokens falls to $0.97, continuing months‑long decline from $2.07 peak on May 28
| Source: Techmeme | Original article
The LLM Token Expenditure Index shows the average cost per million tokens dropped to 97 cents, continuing a steep decline from a May 28 peak of $2.07.
The LLM Token Expenditure Index – a daily benchmark that aggregates the weighted‑average price users pay for a million large‑language‑model tokens across providers – has slipped to 97 cents, according to CNBC’s Alex Harring. The drop follows a steep, months‑long slide that began after the index peaked at $2.07 per million tokens on May 28.
The index, published each trading day under the ticker SDLLMTK, reflects the market‑wide cost of inference regardless of model or vendor. Its recent trajectory marks the seventh straight day of decline, a trend that has sparked unease on Wall Street, where analysts have warned that volatile token pricing could destabilise AI‑driven business models.
Lower token prices matter because they directly affect the operating expenses of companies that rely on generative AI, from cloud‑based SaaS platforms to niche startups. A sub‑dollar cost per million tokens could ease budget pressures that have been highlighted in recent coverage of AI personalization costs and the high‑profile token‑billing debates on the exchange floor. Cheaper inference may also broaden the economic case for deploying more sophisticated models in production, potentially accelerating adoption in sectors such as agriculture, software development and media.
Investors and industry watchers will now monitor whether the downward momentum sustains or rebounds. Key signals include any adjustments in provider pricing structures, the emergence of new caching or batch‑discount mechanisms, and the response of AI‑heavy firms to the softened cost environment. The index’s next moves will offer a real‑time gauge of how affordable large‑scale language‑model usage is becoming, and whether the current lull signals a longer‑term shift in AI economics.
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