Gavin Baker (@GavinSBaker)

We are going to see a lot of vertically focused AI native companies accelerate. Routers, open-source models and specialized post-training enabled by companies like @FireworksAI_HQ have all made dramatic advances and the combination of the three is driving accelerating growth. Companies like @wearelegora can now use their data to post-train an open-source model and then combine it with frontier models behind a router to get the same or better outcomes at lower costs than the frontier alone. This dramatically improves the business model for all these companies. @cognition seeing similar trends.

Nvidia is the leading open source AI company by a wide margin. The silliness of this post is compounded by the fact that the letter did not suggest that closed source AI companies should open source their models.

New Pareto Frontier: Grok 4.5, SWE-1.7 and Opus 5. Intelligence per $ will be the only metric that matters over time. K3 probably joins the frontier once available on the inference clouds.

The mega bull case for AI infrastructure would be *if* market share shifted away from certain frontier labs with 90%+ inference margins toward cheaper models, whether open-source or closed. It would increase the ROI on AI spend for end customers by increasing intelligence per dollar, which would drive incremental token demand. Margin dollars would effectively get redistributed from the frontier labs to AI infrastructure providers. The infra winners would be those with the lowest per token cost and the winners at the model layer would be those with the highest token efficiency. There are many reasons Jensen is so focused on open source, but this is likely the most important one as I think he is probably less worried about a monopsony these days. Lower margin % at the model layer = more margin $ at the infra layer all else equal. With SpaceX and Meta being vertically integrated and possessing the #3# and #4# models respectively it is more possible than ever. Note that Grok 4.5 is ahead of Fable for some useful tasks at a much lower cost, so ranking them #3# is conservative. This is not happening yet. Cheap, mostly open source tokens are likely the majority of volume today but the majority of economic value is still accruing to the most intelligent models. Might change though. We will see.

Grok 4.5. Pareto dominant for coding by the numbers. We will see on the all-important vibes. Instinct is the benchmarks are likely directionally accurate given the stated focus on real world utility.

Composer 2.5 being Pareto dominant in coding per CursorBench is important. This is after only a few weeks of supplemental training and/or RL in the Colossus 2 cluster.   The 1.5 trillion parameter version of Grok will likely be a much better base model than Kimi. We shall see.