Codex.

Codex CLI is OpenAI’s terminal agent. It speaks the OpenAI format, which is the same one NaN speaks, so it connects directly: all you have to do is declare a new provider.

You can skip all of this The NaN CLI writes this configuration for you: Setup tab, e to paste your key, space to mark Codex, c to apply.

What you need

• Codex CLI installed.
• Your NaN API key in an environment variable.

export NAN_API_KEY="sk-your-key"

Codex reads the key from the environment variable you point it at, not from the configuration file. That way it does not end up written in a file you might push to a repository by accident.

Configuration

Edit ~/.codex/config.toml:

model_provider = "nan"
model = "glm5.3-flash"

[model_providers.nan]
name = "NaN"
base_url = "https://api.nan.builders/v1"
env_key = "NAN_API_KEY"
wire_api = "chat"

Three details that matter:

• wire_api = "chat" makes Codex use /chat/completions. That is what you want: the cluster’s /responses endpoint answers in one go instead of streaming, so with "responses" you would see the answer appear all at once at the end.
• The provider identifier cannot be openai, ollama or lmstudio, which are reserved. That is why it is called nan.
• base_url ends at /v1 and nothing more. Do not add the endpoint path.

Check that it works

codex

Ask it for something short, for example to list the files in the directory and summarize what the project does. If it answers, it is already working against the cluster.

If you see an authentication error, the usual cause is that NAN_API_KEY is not exported in the terminal you are launching codex from.

Switching models

You can change it without touching the file:

codex --model deepseek-v4-flash

Or leave several providers declared and pick with --profile if you prefer separate profiles per task.

Recommended model

glm5.3-flash for coding work. If you have the premium tier, glm5.3. For one-off questions that do not touch files, deepseek-v4-flash is more than enough.