Noam Brown· @polynoamial · X·· 2026-08-17AI 评分34
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Noam Brown 称赞 Codex 的自动压缩功能出色,并指出若需 1M-token 上下文,可通过配置实现。
正文 · 原文
Autocompaction in Codex is really good. @OpenAI recognized early on that it would be important and invested in research efforts to make it near-seamless. But if you want 1M-token context, it's an option.
Here is how to enable a 1M-token context window in Codex for GPT-5.6 Sol. Even though we have tuned the context limit in Codex to be set optimally when it comes to performance and cost, this is a common ask, so here it is documented. A larger context window lets Codex retain more code, tool output, and conversation history before summarizing older material. You need a model that supports it. And GPT-5.6 Sol, for example, has a documented 1,050,000-token window. Open ~/.codex/config.toml and add or update these settings at the top level, before any [section] headers: ``` model = "gpt-5.6-sol" model_context_window = 1000000 model_auto_compact_token_limit = 900000 ``` The first setting selects the model. The second tells Codex to use a one-million-token context budget. The third starts automatic history compaction around 900,000 tokens, leaving some headroom. Restart Codex client and start a new session after saving. To try the configuration for a single CLI session without changing your defaults: ``` codex -m gpt-5.6-sol \ -c model_context_window=1000000 \ -c model_auto_compact_token_limit=900000 ``` Have fun, but also know that we tuned the default carefully!在 X 查看被引用的帖子
来源:Noam Brown · x.com