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| parent | nav_order |
|---|---|
| Connecting to LLMs | 900 |
Model warnings
Aider supports connecting to almost any LLM, but it may not work well with less capable models. If you see the model returning code, but aider isn't able to edit your files and commit the changes... this is usually because the model isn't capable of properly returning "code edits". Models weaker than GPT 3.5 may have problems working well with aider.
Aider tries to sanity check that it is configured correctly to work with the specified model:
- It checks to see that all required environment variables are set for the model. These variables are required to configure things like API keys, API base URLs, etc.
- It checks a metadata database to look up the context window size and token costs for the model.
Sometimes one or both of these checks will fail, so aider will issue some of the following warnings.
Missing environment variables
Model azure/gpt-4-turbo: Missing these environment variables:
- AZURE_API_BASE
- AZURE_API_VERSION
- AZURE_API_KEY
You need to set the listed environment variables. Otherwise you will get error messages when you start chatting with the model.
Unknown which environment variables are required
Model gpt-5: Unknown which environment variables are required.
Aider is unable verify the environment because it doesn't know which variables are required for the model. If required variables are missing, you may get errors when you attempt to chat with the model. You can look in the litellm provider documentation to see if the required variables are listed there.
Unknown model, did you mean?
Model gpt-5: Unknown model, context window size and token costs unavailable.
Did you mean one of these?
- gpt-4
If you specify a model that aider has never heard of, you will get an "unknown model" warning. This means aider doesn't know the context window size and token costs for that model. Some minor functionality will be limited when using such models, but it's not really a significant problem.
Aider will also try to suggest similarly named models, in case you made a typo or mistake when specifying the model name.