OpenAI’s Jalapeño inference chip posts 1.5–1.9× better perf/watt than Blackwell in first benchmarks

[AINews] Hot Chips: OpenAI’s Jalapeño, Cerebras CS-5, Groq 3 LPX, Apple M6

OpenAI shared first benchmarks for its custom inference chip Jalapeño at Hot Chips 37. Against NVIDIA GB200/GB300, Jalapeño delivered 1.5–1.9× more work per watt at peak throughput, 1.7–3.6× lower end-to-end latency, and 2.1–4.1× higher performance on highly interactive workloads. The chip is rated at 700W but reportedly stayed at or below 550W in tested runs. OpenAI plans to deploy it into its own infrastructure by year-end, with Gen 2 deep in development and Gen 3 underway. Separately, GPT-Astra + Codex helped optimize low-level kernels, getting three previously unplanned open-weight models to run 1.5–1.8× faster than human-expert-written code in about two months. SemiAnalysis called it unusually strong for a first-gen ASIC. The post does not disclose pricing, volume, or external customer plans.

Why it matters: OpenAI dropped real silicon benchmarks at Hot Chips, claiming 1.5-1.9x perf/watt and 1.7-3.6x lower latency vs. NVIDIA's GB200/GB300. This is the first hard evidence that their custom chip effort is real and competitive. The slight discount is because we only have Latent Space...