Broadcom · OpenAI · Nvidia · GPT · DeepSeek · Tom's Hardware
OpenAI’s 700W Jalapeño ASIC outpaces 1,400W Nvidia flagship GPU
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Over one week after Nvidia agreed to backstop up to $105 billion in financing for its data centers, OpenAI arrived at Hot Chips on Tuesday with benchmarks claiming its first in-house chip beats Nvidia's GB300.
Key facts
- On August 17, Nvidia agreed to provide up to $105 billion in financing for an OpenAI-leased data center campus in Ohio
- Each Jalapeño package, unveiled in June after a nine-month RTL-to-tapeout cycle, pairs its compute die with six HBM4 stacks, totaling 216 GiB at 15.4 TB/s
- The GB300 carries 288GB of HBM3E at a 1,400W rating, so per watt of rated power, OpenAI's chip packs roughly 50% more memory
- Over one week after Nvidia agreed to backstop up to $105 billion in financing for its data centers, OpenAI arrived at Hot Chips on Tuesday with benchmarks claiming its first in-house chip beats
Summary
The tests covered three open models: GPT-OSS 120B, DeepSeek R1 670B, and Moonshot AI's 1-trillion-parameter Kimi K2.5, with OpenAI reporting its widest leads at low-latency operating points, where it claims 8.6 times to 104.3 times more throughput per kilowatt at the GB300's fastest previous time-between-tokens settings. OpenAI normalized the results to each accelerator's published package TDP, though it said Jalapeño's measured sustained power stayed at or below 550W in testing. Jalapeño wasn't tested against Vera Rubin, the Nvidia platform that's slated to power the first gigawatt of Nvidia systems OpenAI agreed to deploy in the second half of 2026. Each Jalapeño package, unveiled in June after a nine-month RTL-to-tapeout cycle, pairs its compute die with six HBM4 stacks, totaling 216 GiB at 15.4 TB/s.