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Large Language ModelsAI Business & IndustrySimon Willison's WeblogPublished: Nov 12, 2026, 01:00 JST

Anthropic IPO video: Claude runs on all four chip families

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Anthropic IPO video: Claude runs on all four chip families

3 Key Points

  1. What happened

    In Anthropic's IPO roadshow video, co-founder Tom Brown said Claude trains and serves across AWS Trainium, Google TPUs, NVIDIA GPUs and AMD GPUs, and that Claude ported or wrote almost 100% of the kernels to get running on AMD in three days.

  2. Why it matters

    Brown presents that multi-chip bet, plus stacked compute multipliers, as a hard-to-replicate edge—suggesting Anthropic can get more effective compute from the same physical capacity, a claim investors may weigh as the IPO roadshow unfolds.

WHO IT HITSInvestors evaluating Anthropic's IPO get a rare public look at how the company sources compute across four chip vendors, while engineers weighing multi-chip software stacks see a claimed precedent of porting work done largely by Claude itself.

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Context & Analysis

The roadshow video is notable less for the IPO mechanics than for what Anthropic chose to disclose about its compute stack. Brown frames the early multi-chip bet as unconventional—many people thought running AI models on different chips wasn't worth the effort, since each chip needs its own tailored software and inference stack—and says the company has been doing it for years. The AMD example is the concrete proof point: where bringing on a new chip platform had taken dozens of engineers months, Claude got it running in three days with basically no human intervention.

Brown pairs that with a second driver: the rate at which Anthropic discovers compute multipliers, which he describes as multiplying physical capacity to raise total effective compute. He argues these multipliers stack—each new one has a positive effect on the earlier ones—and that the process could accelerate toward recursive self-improvement, with Claude discovering multipliers entirely by itself. That is a forward-looking claim from Anthropic's co-founder, not an established result.

A prior hint: last September's postmortem of three recent issues described bugs that affected just Anthropic's TPU deployments, an early sign of the multi-chip approach in practice.

FAQ
Which chips does Anthropic say it uses to train and serve Claude?
All four major chip families: AWS Trainium, Google TPUs, NVIDIA GPUs and AMD GPUs, according to co-founder Tom Brown in the roadshow video.
How did Anthropic get Claude running on AMD GPUs?
Brown said the company had Mythos try it, and Claude was running on AMD in just three days with basically no human intervention, porting or writing almost 100% of the kernels.
What is a compute multiplier?
As Brown describes it, a 4x multiplier means 25 units of compute can train the same model that would otherwise need 100 units—or 100 units can train a model that previously required 400.
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