# Model Providers
URL: /models

import { Card, Cards } from "fumadocs-ui/components/card";

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:

| Provider      | Description                                                                        | Best For                                                            |
| ------------- | ---------------------------------------------------------------------------------- | ------------------------------------------------------------------- |
| **OpenAI**    | Industry-leading models including GPT-4.1, GPT-5, GPT-5.1, and o3 reasoning models | General-purpose tasks, reasoning, and state-of-the-art performance  |
| **Anthropic** | Claude models with strong safety and reasoning capabilities                        | Complex reasoning, analysis, and safety-critical applications       |
| **Google**    | Gemini models with multimodal support and extended thinking capabilities           | Multimodal tasks, vision-based applications, and advanced reasoning |
| **Groq**      | High-speed inference with Llama models optimized for throughput                    | Low-latency applications and real-time processing                   |
| **Mistral**   | Fast, efficient open-source models with strong performance                         | Cost-effective alternatives with reliable performance               |

## Configuring Providers

All model providers are configured through your Tambo Cloud dashboard:

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

<Callout type="tip" title="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.
</Callout>

## 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](/models/labels).

<Callout type="warning" title="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.
</Callout>

## 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](/models/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](/models/reasoning-models) for detailed configuration guides.

## Quick Links

<Cards>
  <Card href="/models/labels" title="Model Labels & Status">
    Understand model testing status and known behaviors
  </Card>

  <Card href="/models/custom-llm-parameters" title="Custom Parameters">
    Fine-tune model behavior with temperature, tokens, and more
  </Card>

  <Card href="/models/reasoning-models" title="Reasoning Models">
    Configure advanced reasoning capabilities for complex tasks
  </Card>
</Cards>

## 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](/api-reference) and [Concepts](/concepts) sections.