OpenAI has released benchmark results for its custom inference chip, codenamed "jalapeño," which it developed in collaboration with Broadcom. The chip reportedly outperforms NVIDIA's GB300 and GB200 systems in throughput per kilowatt and end-to-end latency, particularly for OpenAI's own models like GPT-OSS 120B. This integrated system approach, combining hardware, memory, networking, and serving software, aims to reduce data movement and latency, which is crucial for agentic AI applications. While the chip is not designed for training and NVIDIA's newer platforms were not included in the test, OpenAI plans to deploy jalapeño in its own data centers starting in late 2026. AI
IMPACT This development signals OpenAI's strategic move towards custom hardware, potentially reducing reliance on external GPU providers and optimizing performance for AI workloads.
RANK_REASON OpenAI, a frontier lab, released benchmarks for its custom inference chip 'jalapeño'. [lever_c_demoted from frontier_release: ic=1 ai=0.7]
- Broadcom
- Codex
- DeepSeek R1 670B
- GB200
- GB300
- GPT-OSS 120B
- InferenceX
- jalapeño
- Kimi K2.5 1T
- NVIDIA
- OpenAI
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