# 字节跳动开发自研CPU芯片，以支持AI智能体大规模部署

- 来源：Rohan Paul (@rohanpaul_ai)
- 发布时间：2026-05-30 16:54
- AIHOT 分数：63
- AIHOT 链接：https://aihot.virxact.com/items/cmps4zs3a06vlslljf7rwxxbo
- 原文链接：https://x.com/rohanpaul_ai/status/2060645982954819659

## AI 摘要

路透社报道称，字节跳动正开发自研数据中心CPU芯片，以支持TikTok规模的AI智能体运行。此举受Groq的“语言处理单元”启发，旨在应对当前服务器处理器短缺问题。公司正在测试Arm和RISC-V两种架构，以比较成熟商业设计与可控开放指令集。由于CPU价格季度性上涨10%-35%且供应链延迟，开发自研芯片已成为一项成本与供应链策略，旨在减少对受限外国AI硬件的依赖并降低单次查询推理成本。AI智能体的推理对CPU依赖远大于传统模型，因单个用户请求可能触发多个步骤。据报道，字节跳动可能依赖外部合作伙伴进行芯片设计与制造。

## 正文

Reuter： ByteDance is building its own AI data-center CPUs because running agents at TikTok scale now depends on scarce server processors， not only Nvidia GPUs.

inspired by Groq's "language processing units，" they are testing both Arm and RISC-V， which lets it compare a mature commercial design against a more controllable open instruction set before mass production.

The market is seeing a 10%-35% quarterly CPU price increases and long supply delays， hence making an in-house silicon is now cost and supply-chain move， not just a prestige project.

So ByteDance wants to both reduce dependence on restricted foreign AI hardware and make inference cheaper per query.

The deeper shift is that AI agents is now turning CPUs into strategic chips. A
gentic inference stresses CPUs much more because one user request can trigger many smaller steps： retrieve files， call a tool， query a database， run a model， check the answer， call another model， send data across servers， and manage memory.

However， ByteDance does not seem to have in-house chip design teams and is reportedly relying on several external partners， who are also expected to handle the actual silicon manufacturing.

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reuters .com/world/china/bytedance-developing-custom-cpu-chips-support-ai-rollout-sources-say-2026-05-28/