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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallOpenAI’s Jalapeño inference chips are reportedly being deployed with AMD EPYC Turin CPUs as their hosts, with 1.5 TB of memory per host. OpenAI hardware chief Richard Ho told Tom’s Hardware that Turin was a pragmatic, lower-risk choice: the platform was mature and partners already had experience with it, while NVIDIA Vera, considered as a standalone CPU, was “a little bit behind” on maturity at the time. That is a project-specific explanation—not a claim that Vera is universally slower or inferior.
What is hosting OpenAI’s Jalapeño ASICs?
Tom’s Hardware reported on October 2, 2026, that OpenAI is deploying its Jalapeño inference ASICs internally alongside AMD EPYC Turin CPUs, with 1.5 TB of memory per host. The report attributes the configuration to an interview with OpenAI VP and Head of Hardware Richard Ho. OpenAI’s own announcement and results page describe the accelerator and deployment preparation, but do not state this specific host configuration. The report does not name the exact EPYC model or SKU, and the 1.5 TB figure has not been independently verified in the sources cited here. Tom’s Hardware’s October 2 report
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Why did OpenAI choose Turin?
Ho described the decision as a way to de-risk the design and move quickly without giving up on performance and cost goals. Turin was sufficiently mature for the project, and OpenAI’s partners had experience with it. Those factors can reduce integration and schedule risk when a team is building a new accelerator system.
Ho’s comment about Vera was narrowly qualified: “Vera, as a standalone, is a little bit behind on that maturity level.” He also said, “The Turing device is strong. It did what we needed to do, and partly our partners had some experience with it,” in the Tom’s Hardware interview. The report renders “Turing device” in the quote; it should not be silently changed when quoting, though the surrounding report is about AMD’s Turin platform. His statement reflects the maturity assessment for this project at the time of the interview, not a general comparison of CPU performance.
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Jalapeño and Vera have different jobs
Jalapeño is an OpenAI-designed accelerator intended for large-language-model inference, not a general-purpose CPU. OpenAI says it developed the chip with Broadcom, which contributed to silicon implementation, networking, and connectivity, and Celestica, which worked on boards, racks, and systems. OpenAI calls Jalapeño the first accelerator in a multi-generation compute platform and said initial deployment was planned by the end of 2026. OpenAI and Broadcom’s announcement
NVIDIA, by contrast, positions Vera as a custom CPU for agentic AI tasks such as orchestration, tool-calling, reinforcement learning, analytics, sandboxing, and long-context state management. NVIDIA says it can be used in standalone CPU systems or as the host processor in Vera Rubin NVL72. The two chips therefore are not interchangeable products in a like-for-like contest: Jalapeño is the inference accelerator, while Turin or Vera would serve as a CPU in the system. NVIDIA’s product description does not confirm or refute Ho’s time-bound assessment of standalone Vera’s maturity for OpenAI’s project. NVIDIA’s Vera product description
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What OpenAI’s published benchmark results do—and do not—show
OpenAI has published comparisons using InferenceX configurations for GPT-OSS 120B, DeepSeek R1 670B, and Kimi K2.5 1T. These are company-published measurements, not independent tests, and they evaluate accelerator configurations rather than the choice of EPYC Turin as a host.
| Test and stated conditions | OpenAI-reported result | What the figure means |
|---|---|---|
| GPT-OSS 120B; nominal 8k/1k STP setup | Jalapeño at 700 W; GB200 at 1,200 W. Peak mixed throughput per kW: 85,448 versus 44,960. | OpenAI reports approximately 1.9× higher peak mixed throughput per kW for Jalapeño in this setup. |
| DeepSeek R1 MXFP4 | Jalapeño package TDP 700 W; GB300 package TDP 1,400 W. Peak mixed throughput per kW: 19,641 versus 11,781. | OpenAI reports approximately 1.7× higher peak mixed throughput per kW for Jalapeño in this setup. |
The figures should be read with their stated models, configurations, and power conditions; they do not establish that a Turin-hosted system outperforms a Vera-hosted one. OpenAI’s results page says production qualification, software maturation, scale preparation, and validation across more models were still ongoing as it prepared for deployment. That status is more specific than the earlier announcement’s plan for initial deployment by the end of 2026. OpenAI’s Jalapeño results
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What remains unknown about the host system
- The exact EPYC Turin processor model or SKU used in the reported system is not stated.
- The 1.5 TB per-host memory configuration is reported by Tom’s Hardware; the OpenAI pages cited here do not publish it.
- The available reporting does not provide independent deployment records or a direct Turin-versus-Vera host comparison.
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