OpenAI is unsatisfied with some Nvidia chips and looking for alternatives: Reuters
OpenAI seeks SRAM-heavy chips to accelerate AI coding tasks, targeting 10% of inference needs amid delayed Nvidia investment and new deals with AMD and Cerebras.
- On February 2, 2026, Reuters reported OpenAI is unsatisfied with some Nvidia AI chips and has sought alternatives since last year, complicating ongoing investment talks between the companies.
- OpenAI's strategy shift toward inference led it to seek SRAM-heavy chips since last year, as embedded memory speeds responses by reducing latency compared with Nvidia and AMD external memory.
- OpenAI negotiated with startups including Cerebras and Groq and struck a commercial deal with Cerebras last month, while Nvidia licensed Groq's technology in a $20-billion deal that ended OpenAI's talks.
- Altman emphasized speed for coding users, saying they will `put a big premium on speed for coding work`, and OpenAI expects new hardware to supply about 10% of inference needs while relying on Cerebras to meet demand.
- Nvidia remains dominant in training chips as inference gains importance, with rivals Anthropic and Google deploying TPUs while Nvidia says customers choose its inference for performance and cost.
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Exclusive: OpenAI is unsatisfied with some Nvidia chips and looking for alternatives, sources say
OpenAI is unsatisfied with some of Nvidia’s latest artificial intelligence chips, and it has sought alternatives since last year, eight sources familiar with the matter said, potentially complicating the relationship between the two highest-profile players in the AI boom.
OpenAI says its unhappy with Nvidia inference hardware, now looking at AMD, Cerebras, Groq
OpenAI isn’t happy with Nvidia’s AI chips anymore, especially when it comes to how fast they can answer users. The company started looking for other options last year, and now it’s talking to AMD, Cerebras, and was even talking to Groq before that got shut down. This tension started getting real when OpenAI realized Nvidia’s chips weren’t fast enough for specific things like writing code and handling software-to-software tasks. One insider alleg…
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