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LibreChat provides comprehensive support for AI models from multiple providers, giving you the flexibility to choose the right model for your specific use case.

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Supported Providers

LibreChat integrates with all major AI providers through a unified interface:

OpenAI

GPT-4o, GPT-4, GPT-3.5, and DALL-E models

Anthropic

Claude 4.5 Sonnet, Claude 3.7 Sonnet, and other Claude models

Google

Gemini Pro, Gemini Flash, and PaLM models

Azure OpenAI

Azure-hosted OpenAI models with custom deployments

AWS Bedrock

Access to Anthropic, Meta, Cohere, AI21, Mistral, and more

Custom Endpoints

Connect to any OpenAI-compatible API

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Provider Configuration

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OpenAI

Configure OpenAI models in your librechat.yaml:
librechat.yaml
endpoints:
  openAI:
    # Models are fetched automatically from the API
    # Optional: titleModel for conversation titles
    titleModel: "gpt-4o-mini"

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Anthropic

Set up Claude models with custom parameters:
librechat.yaml
endpoints:
  anthropic:
    streamRate: 20
    titleModel: claude-3.5-haiku
    # Vertex AI configuration for Claude on Google Cloud
    vertex:
      region: "us-east5"
      models:
        claude-opus-4.5:
          deploymentName: claude-opus-4-5@20251101
        claude-sonnet-4:
          deploymentName: claude-sonnet-4-20250514

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Google (Gemini)

Configure Google’s Gemini models:
librechat.yaml
endpoints:
  google:
    models:
      default:
        - "gemini-2.0-flash-exp"
        - "gemini-1.5-pro"
        - "gemini-1.5-flash"

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AWS Bedrock

Access multiple providers through AWS:
librechat.yaml
endpoints:
  bedrock:
    models:
      - "anthropic.claude-3-7-sonnet-20250219-v1:0"
      - "anthropic.claude-3-5-sonnet-20241022-v2:0"
    
    # Inference Profiles for cross-region routing
    inferenceProfiles:
      "us.anthropic.claude-sonnet-4-20250514-v1:0": "${BEDROCK_INFERENCE_PROFILE_CLAUDE_SONNET}"
    
    # Guardrail configuration
    guardrailConfig:
      guardrailIdentifier: "your-guardrail-id"
      guardrailVersion: "1"
      trace: "enabled"

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Custom Endpoints

Connect to any OpenAI-compatible API:
librechat.yaml
endpoints:
  custom:
    # Groq Example
    - name: 'groq'
      apiKey: '${GROQ_API_KEY}'
      baseURL: 'https://api.groq.com/openai/v1/'
      models:
        default:
          - 'llama3-70b-8192'
          - 'llama3-8b-8192'
          - 'mixtral-8x7b-32768'
      titleConvo: true
      titleModel: 'mixtral-8x7b-32768'
      modelDisplayLabel: 'groq'
    
    # Mistral AI Example
    - name: 'Mistral'
      apiKey: '${MISTRAL_API_KEY}'
      baseURL: 'https://api.mistral.ai/v1'
      models:
        default: ['mistral-tiny', 'mistral-small', 'mistral-medium']
        fetch: true
      titleConvo: true
      titleModel: 'mistral-tiny'
      modelDisplayLabel: 'Mistral'
      dropParams: ['stop', 'user', 'frequency_penalty', 'presence_penalty']
    
    # OpenRouter Example
    - name: 'OpenRouter'
      apiKey: '${OPENROUTER_KEY}'
      baseURL: 'https://openrouter.ai/api/v1'
      models:
        default: ['meta-llama/llama-3-70b-instruct']
        fetch: true
      titleConvo: true
      dropParams: ['stop']
      modelDisplayLabel: 'OpenRouter'

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Model Features

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Multimodal Support

Many models support vision and file analysis:
  • GPT-4o: Images, documents, and vision
  • Claude 4.5 Sonnet: Advanced multimodal understanding
  • Gemini 2.0 Flash: Native multimodal processing
  • Claude 3.7 Sonnet: Document and image analysis
Models that support direct PDF and document processing:
  • OpenAI models (with Responses API)
  • Anthropic Claude models
  • Google Gemini models
  • AWS Bedrock Anthropic models
  • Custom endpoints (provider-dependent)

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Model Parameters

Customize model behavior with parameters:
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temperature
number
default:"1"
Controls randomness. Lower values (0.1-0.5) are more focused and deterministic. Higher values (0.8-1.5) are more creative.
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top_p
number
default:"1"
Nucleus sampling. Alternative to temperature for controlling randomness.
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max_tokens
number
Maximum number of tokens to generate in the response.
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frequency_penalty
number
default:"0"
Reduces repetition of token sequences. Range: -2.0 to 2.0.
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presence_penalty
number
default:"0"
Increases likelihood of talking about new topics. Range: -2.0 to 2.0.

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Advanced Configuration

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Model Specifications

Create preset configurations with Model Specs:
librechat.yaml
modelSpecs:
  list:
    # Grouped under an endpoint
    - name: "gpt-4o"
      label: "GPT-4 Optimized"
      description: "Most capable GPT-4 model with multimodal support"
      group: "openAI"
      preset:
        endpoint: "openAI"
        model: "gpt-4o"
    
    # Custom group with icon
    - name: "coding-assistant"
      label: "Coding Assistant"
      description: "Specialized for coding tasks"
      group: "my-assistants"
      groupIcon: "https://example.com/icons/assistants.png"
      preset:
        endpoint: "openAI"
        model: "gpt-4o"
        instructions: "You are an expert coding assistant..."
        temperature: 0.3
    
    # Standalone (no group)
    - name: "general-assistant"
      label: "General Assistant"
      description: "General purpose assistant"
      preset:
        endpoint: "openAI"
        model: "gpt-4o-mini"

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Parameter Handling

Control which parameters are sent to each endpoint:
librechat.yaml
endpoints:
  custom:
    - name: 'MyEndpoint'
      # Add custom parameters
      addParams:
        safe_prompt: true
      
      # Drop parameters not supported by the endpoint
      dropParams: ['stop', 'user', 'frequency_penalty']
      
      # Add custom headers
      headers:
        x-custom-header: 'value'

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Model Fetching

Automatically fetch available models from the API:
librechat.yaml
endpoints:
  custom:
    - name: 'MyEndpoint'
      models:
        default: ['model-1', 'model-2']
        fetch: true  # Fetch models from /v1/models endpoint

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Model Selection UI

LibreChat provides an intuitive model selection interface:
1

Select Endpoint

Choose your AI provider from the endpoint dropdown
2

Choose Model

Select from available models for that endpoint
3

Configure Parameters

Adjust temperature, tokens, and other settings
4

Start Chatting

Begin your conversation with the selected model

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Best Practices

API Key Security: Always use environment variables for API keys. Never commit credentials to version control.
Model Selection:
  • Use GPT-4o for complex reasoning and multimodal tasks
  • Use GPT-4o-mini for faster, cost-effective responses
  • Use Claude for long context and detailed analysis
  • Use Gemini Flash for speed and efficiency
Token Limits: Different models have different context windows:
  • GPT-4o: 128k tokens
  • Claude 4.5 Sonnet: 200k tokens
  • Gemini 2.0 Flash: 1M tokens

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Environment Variables

Required environment variables by provider: 
OPENAI_API_KEY=sk-...

Agents

Use AI models with autonomous agents

Multimodal

Image and file analysis with vision models

Image Generation

Generate images with DALL-E and other models

Code Interpreter

Execute code with AI assistance

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