# OpenAI 发布首款定制芯片 Jalapeño，由博通制造

- 来源：Hacker News 热门（buzzing.cc 中文翻译）
- 作者：jamdesk
- 发布时间：2026-06-25 02:36
- AIHOT 分数：57
- AIHOT 链接：https://aihot.virxact.com/items/cmqsfte4z02q5slfu9c03t5l1
- 原文链接：https://techcrunch.com/2026/06/24/openai-unveils-its-first-custom-chip-built-by-broadcom

## AI 摘要

OpenAI 本周三发布首款定制推理处理器 Jalapeño，由博通制造，OpenAI 自有 AI 模型参与了芯片开发。该芯片专为推理系统设计，早期测试显示单位功耗性能显著优于当前业界替代方案，运行实时编码模型时运营成本低。此举旨在降低对 NVIDIA GPU 的依赖，并优化 Codex 等 Agent 产品及底层基础设施。OpenAI 正从芯片架构、内核、内存系统到部署体验进行全栈协同优化，以使模型更快、更可靠、更经济。

## 正文

On Wednesday, OpenAI unveiled its first custom-built inference processor, designed and manufactured in collaboration with Broadcom. Named Jalapeño, the new processor was designed specifically for the unique needs of OpenAI’s inference systems. OpenAI’s own AI models assisted in the development of the chip, the company said.

While the chip is still being tested, OpenAI says early results show significantly better performance-per-watt than current state-of-the-art alternatives.

The partnership was officially announced in October, but OpenAI’s chip plans have long been rumored as a way to reduce the company’s dependence on Nvidia’s GPUs. Google and Amazon have both built custom chips to serve a similar purpose, often called “AI accelerators” — silicon designed specifically to speed up machine learning workloads.

OpenAI president Greg Brockman explained the company’s approach to chip development on its in-house podcast, shortly after the Broadcom partnership was announced.

“We have a deep understanding of the workload,” Brockman said in the episode. “We’ve really been looking for specific workloads that are underserved, [and asking] how can we build something that will be able to accelerate what’s possible?”

Jalapeño is specifically designed for inference, the process of running pre-built AI models in response to user commands. In the announcement, OpenAI emphasized the chip’s low operating cost when running real-time coding models. It’s likely that more performance-intensive tasks like pre-training will still rely on Nvidia hardware, but even small reductions in inference costs could do a lot to improve the company’s bottom line.

Optimizing that inference system may prove to be a crucial factor in the economics of AI going forward — and it’s likely to take place at every level of the stack. OpenAI is already building agentic products like Codex and the models that power them, as well as data centers to run those models. Moving into purpose-built chips lets the company go even further in that process, as the company explained in its announcement.

“OpenAI is not only developing frontier models or building products on top of them; it is designing the infrastructure underneath them: chip architecture, kernels, memory systems, networking, scheduling, deployment systems, and product experience,” the company wrote. “Because OpenAI operates across the stack, each layer can be optimized around the same goal: making its models faster, more reliable, and more affordable for users.”