OpenAI Unveils In-House 'Jalapeño' Chip Benchmarks Outperforming Nvidia Blackwell
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OpenAI on Tuesday published benchmark results for its first in-house artificial intelligence processor, codenamed Jalapeño, developed in partnership with Broadcom. The custom application-specific integrated circuit (ASIC) is engineered specifically for AI model inference rather than general-purpose training. Evaluated on SemiAnalysis’s InferenceX platform across public models including GPT-OSS 120B, DeepSeek R1 670B, and Kimi K2.5 1T, Jalapeño achieved 1.5 to 1.9 times higher output per watt than prevailing commercial systems. On DeepSeek R1, the hardware reduced end-to-end latency by 1.7 to 3.6 times and produced over 700 tokens per second for low-concurrency user workloads. OpenAI confirmed that internal AI tools assisted in the chip’s physical layout, bring-up, and code optimization. Rated at 700 watts TDP with sustained drawing below 550 watts, deployment into primary infrastructure is scheduled for late 2026 alongside continued use of external accelerators.
Timeline
- On October 2025 OpenAI partnered with Broadcom to co-design custom computing accelerators.
- On November 2025 engineers started nine-month physical tapeout process for custom silicon.
- On June 24 2026 OpenAI publicly revealed development of custom Jalapeño inference silicon.
- On August 25 2026 (19:00 UTC) OpenAI published official Jalapeño benchmark metrics on InferenceX.
- On August 25 2026 (20:00 UTC) SemiAnalysis confirmed performance metrics and comparison data against Blackwell.
- On August 25 2026 (21:00 UTC) industry analysts evaluated internal custom silicon economics versus merchant GPUs.
- By December 2026 OpenAI expects first-generation Jalapeño chips to begin infrastructure integration.
- By June 2027 initial volume deployment of Jalapeño servers will expand capacity.
- By December 2027 second-generation OpenAI inference silicon is scheduled for deployment readiness.
- By December 2028 multi-generation custom chip program targets ten gigawatts total compute.
Sources
JQJO Editorial Desk · Human reviewed · AI assisted. Report a correction.



























