Use apimodels in OpenAI Codex

Get running in 3 steps

1. 1

   Grab an API key

   Open Console in your console and create an sk_… key.

2. 2

   Drop the config

   Paste the snippet below into ~/.codex/config.toml (create the file if needed).

3. 3

   Export + run

   Export your key, then just run codex.

Full config

# ~/.codex/config.toml — drop-in, paste as-is
model_provider           = "apimodels"
model                    = "gpt-5.4"          # or "gpt-5.5"
review_model             = "gpt-5.5"          # model used by /review
model_reasoning_effort   = "medium"           # low | medium | high | xhigh
disable_response_storage = true

[model_providers.apimodels]
name     = "apimodels"
base_url = "https://apimodels.app/api/v1"
wire_api = "responses"
env_key  = "APIMODELS_API_KEY"

# put your apimodels key in the env var the config points at,
# then launch codex (add this line to ~/.zshrc to make it stick):
export APIMODELS_API_KEY="sk_…your_key…"
codex

Settings reference

Reasoning effort

Reasoning depth is the reasoning.effort field in the request body (Codex sets it via model_reasoning_effort) — no longer a model-name suffix. All levels share the same per-token price; higher effort just emits more reasoning_tokens (billed as part of output_tokens). When calling the API directly, pass "reasoning": { "effort": "high" }.

30-second sanity check

Before installing Codex, confirm the endpoint and your key work with a single curl:

curl -s https://apimodels.app/api/v1/responses \
  -H "Authorization: Bearer $APIMODELS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.4",
    "input": "Reply with exactly: ok",
    "reasoning": { "effort": "low" },
    "max_output_tokens": 16
  }'

Expected response (truncated):

{
  "id": "resp_...",
  "object": "response",
  "model": "gpt-5.4",
  "status": "completed",
  "output": [{
    "type": "message",
    "role": "assistant",
    "content": [{ "type": "output_text", "text": "ok" }]
  }],
  "usage": {
    "input_tokens": 22,
    "output_tokens": 5,
    "total_tokens": 27
  }
}

HTTP 200 with output[].content[0].text === "ok" means you're good to go.

responses or chat?

gpt-5-4 / gpt-5-5 now work either way. For Codex use wire_api = "responses" — its native mode, which handles reasoning and multi-turn tool calls most cleanly. If your client only speaks OpenAI chat format, wire_api = "chat" against /v1/chat/completions reaches these models too. For ordinary chat models (MiniMax-M2.5, grok-4.2, Claude, Gemini, …) just use chat.

Troubleshooting