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Overview

Codex CLI is OpenAI’s terminal coding agent. It talks to the Responses API, which SaveGate serves at https://api.savegate.ai/v1/responses, so you can run Codex against your SaveGate account with one config file and one environment variable. Nothing about your workflow changes: Codex still reads your files, runs commands, and edits code. Only the endpoint moves.

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Prerequisites

  • Codex CLI installed:
    Already have it? codex update pulls the latest build.
  • A SaveGate API key (starts with sg-)

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Setup

1

Add SaveGate as a model provider

Create or edit ~/.codex/config.toml:
~/.codex/config.toml
wire_api = "responses" is required. Codex defaults to the Chat Completions wire format for custom providers, and the Codex models expect the Responses API.
2

Export your key

Add it to your shell profile (~/.zshrc, ~/.bashrc) so it survives new terminals. env_key in the config names the variable — Codex reads the key from there, so the key itself never goes into the config file.
3

Verify

You should see SAVEGATE_OK. If you do, the agent loop, tool calls, and billing are all working.

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Available models

Every model below was verified by running a complete Codex session against it — file read, tool call, and answer — not just by checking that the endpoint accepts a request. That distinction matters: several models accept a Responses call but break part-way through Codex’s agent loop.
Not usable with Codex, even though they work fine on other SaveGate endpoints:
  • Anthropic and Google models (claude-*, gemini-*) — the session drops into repeated Reconnecting... and never completes. Codex’s agent loop depends on OpenAI-native Responses semantics that translation does not fully reproduce.
  • gpt-5.4-nano, o4-mini — the session errors mid-run in our testing.
  • Other *-codex variants (gpt-5.2-codex, gpt-5.1-codex, gpt-5-codex, codex-mini-latest) — upstream returns Model not found.
Use these models through Chat Completions instead, where they are fully supported.
See Pricing for per-token rates. Codex resends the working context on every turn, so a single session commonly runs to tens of thousands of input tokens — budget accordingly, and prefer gpt-4o-mini or gpt-5.4-mini for routine work.

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Using a separate profile

To keep SaveGate settings out of your default Codex config, put them in their own CODEX_HOME:
Useful when you switch between SaveGate and another provider.

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Known warning

On startup Codex may print:
This is harmless. It comes from Codex’s own built-in model registry, which only recognises models served by its default provider. Sessions run normally — tool calls, streaming, and multi-turn context all work. Setting model_context_window and model_max_output_tokens in config.toml does not silence it; the warning is emitted before those are consulted.

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Troubleshooting

  • Confirm SAVEGATE_API_KEY is exported in the shell you are running Codex from: echo $SAVEGATE_API_KEY
  • SaveGate keys start with sg-. A key in any other format will be rejected.
  • Check the key is active in your dashboard.
Almost always a missing wire_api = "responses" in the provider block. Without it Codex sends Chat Completions payloads to a Responses endpoint.
Model IDs are case-sensitive and must match the table above exactly. gpt-5.3-codex works; gpt-5.3-Codex and codex-5.3 do not.
Codex sends large contexts and reasoning models take time to produce a first token. A minute of silence on a big repository is normal. If nothing arrives after several minutes, re-run with a smaller prompt to isolate the problem.

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What Codex uses

For reference, a Codex session talks to exactly one SaveGate endpoint:
Turns are chained with previous_response_id, so no server-side session state is needed on your side. Codex does not call /v1/models, and does not use the response retrieve, cancel, or delete endpoints.