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Model Providers

Connect and configure AI model providers for your Tambo application.

Tambo supports multiple AI model providers, allowing you to choose the best model for your application's needs. Each provider offers different models with varying capabilities, pricing, and performance characteristics.

Available Providers

Tambo integrates with five major AI providers:

ProviderDescriptionBest For
OpenAIIndustry-leading models including GPT-4.1, GPT-5, GPT-5.1, and o3 reasoning modelsGeneral-purpose tasks, reasoning, and state-of-the-art performance
AnthropicClaude models with strong safety and reasoning capabilitiesComplex reasoning, analysis, and safety-critical applications
CerebrasUltra-fast inference (2,000+ tokens/sec) powered by Wafer-Scale Engine hardwareReal-time applications, high-throughput processing
GoogleGemini models with multimodal support and extended thinking capabilitiesMultimodal tasks, vision-based applications, and advanced reasoning
MistralFast, efficient open-source models with strong performanceCost-effective alternatives with reliable performance

Configuring Providers

All model providers are configured through your Tambo Cloud dashboard:

  1. Navigate to DashboardProjectSettingsLLM Providers
  2. Select your desired provider
  3. Choose a model from the available options
  4. (Optional) Add custom parameters for fine-tuned behavior

Multiple Providers

You can configure multiple providers in a single project and switch between them as needed. This is useful for testing different models or optimizing for different use cases.

Model Status Labels

Each model carries a status label indicating how thoroughly it has been tested with Tambo:

  • Tested - Validated on common Tambo tasks; recommended for production
  • Untested - Available but not yet validated; use with caution and test in your context
  • Known Issues - Usable but with observed behaviors worth noting

For detailed information about each label and specific model behaviors, see Labels.

Streaming Considerations

Streaming may behave inconsistently in models other than OpenAI. We're aware of the issue and actively working on a fix. Please proceed with caution when using streaming on non-OpenAI models.

Advanced Configuration

Custom LLM Parameters

Fine-tune model behavior with custom parameters like temperature, max tokens, and provider-specific settings. This allows you to optimize models for your specific use case—whether you need deterministic responses for analysis or creative outputs for generation.

Common parameters across all providers:

  • temperature - Control randomness (0.0-1.0)
  • maxOutputTokens - Limit response length
  • topP - Nucleus sampling threshold
  • presencePenalty - Encourage staying on topic
  • frequencyPenalty - Reduce repetition

Learn more in Custom LLM Parameters.

Reasoning Models

Advanced reasoning models from OpenAI (GPT-5, GPT-5.1, O3) and Google (Gemini 3.0 Pro, Gemini 3.0 Deep Think) expose their internal thinking process. These models excel at complex problem-solving by spending additional compute time analyzing problems before generating responses.

Configure reasoning capabilities through your project's LLM provider settings to enable:

  • Multi-step problem decomposition
  • Solution exploration and verification
  • Detailed reasoning token access
  • Adaptive thinking time (for supported models)

See Reasoning Models for detailed configuration guides.

Next Steps

  • Getting Started: Choose a provider and configure it in your project settings
  • Optimize Performance: Use custom parameters to fine-tune responses for your use case
  • Explore Reasoning: Enable reasoning on supported models for complex tasks
  • Monitor Usage: Track model performance and costs in your dashboard

For comprehensive API and integration guidance, explore the API Reference and Concepts sections.