Viewpoint: The halving of LLM token prices does not signal a weakening in AI demand; the GPU computing power rental market remains robust with strong demand.
45 minutes ago
Professional data firm Silicon Data published a report noting that the market has recently frequently cited its LLM Token Index as a basis for bearish bets on AI trading, but the index’s decline does not signal a weakening of AI demand or model-layer profits. Silicon Data explained that its LLM Token Index measures the actual price paid per million tokens by API users in its sample — referred to as the "usage-weighted price" — rather than token volume or total spending. The index fell 52% from $2.07 on May 28 to $1 on September 21, but had risen 67% between January and its May peak, meaning price movements alone cannot serve as a direct indicator of AI industry sentiment. The firm pointed out that the recent index decline mainly reflects more tasks being allocated to cheaper, faster models, while AI labs continue rolling out additional mid-tier models. Since tokens do not fully represent AI capabilities, the index also cannot distinguish between model substitution and more efficient agent routing on its own. By contrast, the GPU computing power rental market still shows strong demand. Silicon Data’s data shows that rental prices for H200 GPUs at non-hyperscale cloud providers rose from an average of $2.87 in June to $3.29 currently, hitting $3.32 on September 19; B200 GPUs now trade at $5.76, up 7% year-over-year and 31% year-to-date; B300 GPUs have risen 44% since their launch at the end of April. Silicon Data believes that with the large-scale adoption of agents, the vast majority of tokens in the future will likely come from cheap, fast models, so token prices can continue to decline while total token volume still grows significantly. The firm added that truly high-value tasks will likely remain concentrated on frontier models, and the widespread adoption of AI means demand for computing power could be "more, not less".
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