Why everyone from OpenAI to SpaceX is building their own chips (and turning up the heat on Nvidia)

The detail worth sitting with is Broadcom's role as co-developer on OpenAI's Jalapeño chip. That makes Broadcom, not just Nvidia, a structural winner in the custom silicon wave, and it suggests OpenAI is outsourcing chip design risk rather than building a fully captive fab capability the way Google did with TPUs.

This is largely disconnected from recent activity in our archive, as we have no prior coverage to anchor against here. That said, this story belongs to a longer arc in AI infrastructure: the gradual erosion of Nvidia's pricing power as inference (rather than training) becomes the dominant workload. Inference is more latency-sensitive and cost-sensitive than training, which makes custom silicon economics far more attractive. The firms moving fastest, Google, Apple, and now OpenAI, are all running inference at a scale where even modest per-token cost reductions justify the multi-year chip development investment.

Watch whether any of these custom chips publish third-party inference benchmarks (tokens per second per dollar) against H100 or B200 baselines within the next two quarters. Without that, the cost savings claims remain internal projections, not verified competitive pressure on Nvidia.