Nvidia faces rising competition in AI data center processors as customers build their own chips

Nvidia commands an estimated 81% to 90% of the AI data center accelerator market, a dominance built on years of GPU innovation and the stickiness of its CUDA software ecosystem. AMD, Google, Cerebras, Amazon, Meta, and Microsoft are all investing heavily in alternatives, whether through merchant GPUs, custom silicon, or entirely new architectures. The challengers are getting specific AMD secured deployment commitments of 6 GW each from OpenAI and Meta, plus 2 GW from Anthropic, all for its MI450 series and Helios rack-scale platforms. Cerebras launched its CS-4 rack-scale inference system, claiming 750 PFLOPS of performance, roughly double what its previous generation delivered. Google signed a commercial deal with Marvell Technology on July 29 to expand their custom-silicon partnership. The arrangement included a warrant for 58.97 million Marvell shares. Google is targeting general availability of its TPU v8 by late 2026. Why customers are building their own chips Google has been doing this longest with its Tensor Processing Units. Amazon has its Trainium and Inferentia chips. Meta has been developing custom silicon internally. Microsoft has its Maia AI accelerator. Training runs ...