Nvidia and OpenAI abandon unfinished $100B deal in favour of $30B investment

Re:Nvidia and OpenAI abandon unfinished $100B deal in favour... by coredog64 on Friday February 20, 2026 @09:49AM (#47088694)

My take is it's the inference efficiency. It's one thing to have a huge GPU cluster for training, but come inference time you don't need nearly so much. Having the TPU (and models purpose built for TPU) allows for best cost in serving at hyperscale.

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Re:Nvidia and OpenAI abandon unfinished $100B deal in favour... by martinald on Friday February 20, 2026 @11:33AM (#47090216)

Yes potentially - but the OG TPUs were actually very poorly suited for LLM usage - designed for far smaller models with more parallelism in execution.

They've obviously adapted the design but it's a risk optimising in hardware like that - if there is another model architecture jump the risk of having a narrow specialised set of hardware means you can't generalise enough.

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Re:Nvidia and OpenAI abandon unfinished $100B deal in favour... by zozbot234 on Friday February 20, 2026 @11:35AM (#47090242)

Prefill has a lot of parallelism, and so does decode with a larger context (very common with agentic tasks). People like to say "old inference chips are no good for LLM use" but that's not really true.

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