Use Claude Code with Non-Anthropic Models

This tutorial shows how to use Claude Code with non-Anthropic models like OpenAI, Gemini, and other LLM providers through LiteLLM proxy.

:::info

LiteLLM automatically translates between different provider formats, allowing you to use any supported LLM provider with Claude Code while maintaining the Anthropic Messages API format.

:::

Prerequisites

• Claude Code installed
• API keys for your chosen providers (OpenAI, Vertex AI, etc.)

Installation

First, install LiteLLM with proxy support:

uv tool install 'litellm[proxy]'

Configuration

1. Setup config.yaml

Create a configuration file with your preferred non-Anthropic models:

model_list:
  # OpenAI GPT-4o
  - model_name: gpt-4o
    litellm_params:
      model: openai/gpt-4o
      api_key: os.environ/OPENAI_API_KEY
  
  # OpenAI GPT-4o-mini
  - model_name: gpt-4o-mini
    litellm_params:
      model: openai/gpt-4o-mini
      api_key: os.environ/OPENAI_API_KEY

Set your environment variables:

model_list:
  # Google Gemini
  - model_name: gemini-3.0-flash-exp
    litellm_params:
      model: gemini/gemini-3.0-flash-exp
      api_key: os.environ/GEMINI_API_KEY

Set your environment variables:

model_list:
  # Google Gemini
  - model_name: vertex-gemini-3-flash-preview
    litellm_params:
      model: vertex_ai/gemini-3-flash-preview
      vertex_credentials: os.environ/VERTEX_FILE_PATH_ENV_VAR # os.environ["VERTEX_FILE_PATH_ENV_VAR"] = "/path/to/service_account.json" 
      vertex_project: "my-test-project"
      vertex_location: "us-east-1"

  # Anthropic Claude
  - model_name: anthropic-vertex
    litellm_params:
      model: vertex_ai/claude-3-sonnet@20240229
      vertex_ai_project: "my-test-project"
      vertex_ai_location: "us-east-1"
      vertex_credentials: os.environ/VERTEX_FILE_PATH_ENV_VAR # os.environ["VERTEX_FILE_PATH_ENV_VAR"] = "/path/to/service_account.json" 

Set your environment variables:

model_list:
  # Azure OpenAI
  - model_name: azure-gpt-4
    litellm_params:
      model: azure/gpt-4
      api_key: os.environ/AZURE_API_KEY
      api_base: os.environ/AZURE_API_BASE
      api_version: "2024-02-01"

Set your environment variables:

2. Start LiteLLM Proxy

litellm --config /path/to/config.yaml

# RUNNING on http://0.0.0.0:4000

3. Verify Setup

Test that your proxy is working correctly:

curl -X POST http://0.0.0.0:4000/v1/messages \\
-H "Authorization: Bearer $LITELLM_MASTER_KEY" \\
-H "Content-Type: application/json" \\
-d '{
    "model": "gpt-4o",
    "max_tokens": 1000,
    "messages": [{"role": "user", "content": "What is the capital of France?"}]
}'

curl -X POST http://0.0.0.0:4000/v1/messages \\
-H "Authorization: Bearer $LITELLM_MASTER_KEY" \\
-H "Content-Type: application/json" \\
-d '{
    "model": "gemini-3.0-flash-exp",
    "max_tokens": 1000,
    "messages": [{"role": "user", "content": "What is the capital of France?"}]
}'

curl -X POST http://0.0.0.0:4000/v1/messages \\
-H "Authorization: Bearer $LITELLM_MASTER_KEY" \\
-H "Content-Type: application/json" \\
-d '{
    "model": "gemini-3.0-flash-exp",
    "max_tokens": 1000,
    "messages": [{"role": "user", "content": "What is the capital of France?"}]
}'

curl -X POST http://0.0.0.0:4000/v1/messages \\
-H "Authorization: Bearer $LITELLM_MASTER_KEY" \\
-H "Content-Type: application/json" \\
-d '{
    "model": "azure-gpt-4",
    "max_tokens": 1000,
    "messages": [{"role": "user", "content": "What is the capital of France?"}]
}'

4. Configure Claude Code

Configure Claude Code to use your LiteLLM proxy:

:::tip The LITELLM_MASTER_KEY gives Claude Code access to all proxy models. You can also create virtual keys in the LiteLLM UI to limit access to specific models. :::

5. Use Claude Code with Non-Anthropic Models

Start Claude Code and specify which model to use:

# Use OpenAI GPT-4o
claude --model gpt-4o

# Use OpenAI GPT-4o-mini for faster responses
claude --model gpt-4o-mini

# Use Google Gemini
claude --model gemini-3.0-flash-exp

# Use Vertex AI Gemini
claude --model vertex-gemini-3-flash-preview

# Use Vertex AI Anthropic Claude
claude --model anthropic-vertex

# Use Azure OpenAI
claude --model azure-gpt-4

How It Works

LiteLLM acts as a unified interface that:

1. Receives requests from Claude Code in Anthropic Messages API format
2. Translates the request to the target provider's format (OpenAI, Gemini, etc.)
3. Forwards the request to the actual provider
4. Translates the response back to Anthropic Messages API format
5. Returns the response to Claude Code

This allows you to use Claude Code's interface with any LLM provider supported by LiteLLM.

Advanced Features

Load Balancing and Fallbacks

Configure multiple deployments with automatic fallback:

model_list:
  - model_name: gpt-4o  # virtual model name
    litellm_params:
      model: openai/gpt-4o
      api_key: os.environ/OPENAI_API_KEY
  
  - model_name: gpt-4o  # same virtual name
    litellm_params:
      model: azure/gpt-4o
      api_key: os.environ/AZURE_API_KEY
      api_base: os.environ/AZURE_API_BASE

router_settings:
  routing_strategy: simple-shuffle  # Load balance between deployments
  num_retries: 2
  timeout: 30

Usage Tracking and Budgets

Track usage and set budgets through the LiteLLM UI:

litellm_settings:
  master_key: os.environ/LITELLM_MASTER_KEY
  database_url: "postgresql://..."  # Enable database for tracking
  
general_settings:
  store_model_in_db: true

Start the proxy with the UI:

litellm --config /path/to/config.yaml --detailed_debug

Access the UI at http://0.0.0.0:4000/ui to:

• View usage analytics
• Set budget limits per user/key
• Monitor costs across different providers
• Create virtual keys with specific permissions

Supported Providers

LiteLLM supports 100+ providers. Here are some popular ones for use with Claude Code:

• OpenAI: GPT-4o, GPT-4o-mini, o1, o3-mini
• Google: Gemini 2.0 Flash, Gemini 1.5 Pro/Flash
• Azure OpenAI: All OpenAI models via Azure
• AWS Bedrock: Llama, Mistral, and other models
• Vertex AI: Gemini, Claude, and other models on Google Cloud
• Groq: Fast inference for Llama and Mixtral
• Together AI: Llama, Mixtral, and other open source models
• Deepseek: Deepseek-chat, Deepseek-coder

View full list of supported providers →