Codex Usage: How to Check Your Limits and Make Them Last

Codex usage is measured in credits derived from token consumption rather than message counts, with rolling five-hour and possible weekly limits shared across Codex and certain ChatGPT workplace products. Model selection is presented as the primary cost factor: GPT-5.6 Sol has substantially higher published input and output credit rates than GPT-5.6 Luna, while context size, reasoning, tool use, image generation, fast mode, and repeated prompts can also increase consumption. Users can monitor allowance and session details through the Codex CLI’s `/usage`, `/status`, and configurable `/statusline` commands, or through OpenAI’s usage dashboard, while `codex exec --json` provides per-run token accounting for CI workflows. The guidance recommends using lower-cost models for routine tasks, reducing unnecessary prompt, AGENTS.md, and MCP-server context, using planning and compaction features, and logging JSON usage in automated jobs. It also distinguishes subscription allowances from API-key billing, explains reset and credit options when limits are reached, and argues that external browser-based verification can reduce costly retry cycles by confirming whether application changes work in a real environment.

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