LiteLLM's release notes provide a configuration for registering gpt-6-luna in the proxy model list and describe its GPT-6 request-family compatibility path.
Suitable tasks: Exposing a GPT-6 Luna model alias through LiteLLM Proxy and centrally managing API credentials and routing.
Not suitable for: Mistaking the article's GPT-6 Sol request examples for complete Luna request examples.
Applicable model version: gpt-6-luna.
Applicable clients, agents, or APIs: LiteLLM Proxy; the LiteLLM documentation also mentions the Python SDK.
Recommended reasoning effort and parameters: The article says the default reasoning effort is medium. If using temperature, pair it with reasoning_effort: "none", and verify parameter handling against the LiteLLM version in use.
model_list:
- model_name: gpt-6-luna
litellm_params:
model: openai/gpt-6-luna
api_key: os.environ/OPENAI_API_KEYAdd this entry to config.yaml. The curl and Responses API request examples later in the source use gpt-6-sol, so they are not rewritten or presented here as Luna request examples from the source.
The article says LiteLLM handles GPT-6 model names through the GPT-5 request family, so no separate image upgrade is needed to support max_completion_tokens and reasoning parameters.
The documentation lists support for handling these request parameters starting with v1.101.0; refresh the model cost map as described in the article.
For multi-turn agent workflows, the article recommends using /v1/responses to preserve reasoning state.
This is an integration guide from LiteLLM, not official OpenAI API documentation. Before deployment, check the current LiteLLM version, model mapping, and routing behavior.
This record documents the visible Luna model routing configuration. The API request examples in the source explicitly call Sol and must not be treated as verified Luna calls.
The API key is referenced through an environment variable. Do not put the key value in a configuration file or commit it to the repository.
GPT-6 Luna