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19Opinion

Gavin Baker says cheaper open weight models are good for AI infrastructure as GPU rental prices rise

Open-weight models that decrease margins at the model layer are positive for AI infra, exhibit 1001.2 Since the @Silicon_Data “token index,” which captures both price and mix, peaked on May 31: B300 prices are up 38% B200 prices are up 10% Other GPU indices are up *much* more.

Line chart of the Silicon Data LLM Token Index falling to $0.98 per million tokens while H100, B200 and B300 GPU rental indices rise since May 31, 2026, with B300 up 38.6 percent
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Context

Why it matters

Baker uses Silicon Data's indices to argue that falling token prices are not hurting chip demand: as the cost of AI output drops, rental prices for Nvidia's newest GPUs have kept climbing.

Gavin Baker is the managing partner and chief investment officer of Atreides Management and a well known tech investor. Silicon Data publishes daily benchmarks for GPU rental prices and an LLM Token Expenditure Index that tracks the spend weighted cost of AI tokens. Baker has long argued that cheaper models increase demand for AI compute.

Deep dive

On October 11, Gavin Baker posted that open weight models that decrease margins at the model layer are positive for AI infrastructure, calling his evidence exhibit 1001.2.

He said that since Silicon Data's token index, which captures both price and mix, peaked on May 31, B300 GPU rental prices are up 38 percent and B200 prices are up 10 percent, adding that other GPU indices are up much more.

The chart he shared shows the Silicon Data LLM Token Index falling from a peak above $2 per million tokens around the end of May to $0.98 in October. Over the same period, it shows the B300 rental index up 38.6 percent, the B200 index up 10.2 percent and the H100 index up 3.3 percent, all rebased to 100 on May 31. A note on the chart says the data is based on non hyperscaler cloud providers and that the B300 index begins April 23, 2026.

Baker's argument is that cheaper tokens, driven in part by open weight models, increase usage enough to raise demand for compute, so the value shifts toward the chips and infrastructure that run the models. The post came a day after reports that Nvidia is in talks to acquire or invest further in open weight model lab Reflection AI.

What to expect next

Watch whether GPU rental prices keep rising as token prices fall, and whether the trend holds for hyperscaler pricing, which the chart excludes.

Also watch whether Nvidia's reported talks with Reflection AI lead to a deal, which would put Nvidia more directly behind open weight models that Baker argues drive demand for its chips. Rental prices for the next generation of Nvidia systems will be another test of his thesis once that capacity reaches the market.