本文将指导您如何通过 Ollama、LM Studio 或 llama.cpp 使用本地模型运行 OpenAI Codex 桌面应用。,我们提供了完整的 config.toml 配置示例，帮助您快速搭建环境。,此外，文章还包含了最佳模型推荐、性能基准测试结果以及功能限制的详细图表。
教程
1 min readUpdated May 4, 2026
如何使用本地模型运行 OpenAI Codex 应用（2026 年逐步指南）
通过 Ollama、LM Studio 或 llama.cpp 使用本地模型运行 OpenAI Codex 桌面应用。完整的 config.toml 配置，最佳模型，性能基准和限制图表。
Quick Answer
通过 Ollama、LM Studio 或 llama.cpp 使用本地模型运行 OpenAI Codex 桌面应用。完整的 config.toml 配置，最佳模型，性能基准和限制图表。
Tags:#openai codex#codex 应用#本地模型#ollama#llama.cpp
Evidence & Editorial Standards
- Author: Shahrukh — Creator of PromptSpace, AI researcher & prompt engineer since 2024. 159+ articles published.
- Methodology: Claims in this article are based on hands-on testing with live AI models, publicly available benchmarks, and official model documentation.
- Last tested: Content reviewed and verified against current model versions as of the publication date above.
- Sources: Official model docs, published research, and curated community examples. Links open in context where available.
- Updates: PromptSpace updates articles when models change significantly. Check the "Updated" date in the header for recency.
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Written by Shahrukh
Creator of PromptSpace · AI Researcher & Prompt Engineer
Building the largest free AI prompt library with 4,000+ prompts. Covering AI image generation, prompt engineering, and tool comparisons since 2024. 159+ articles published.