> For the complete documentation index, see [llms.txt](https://docs.hexabot.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.hexabot.ai/faq/which-ai-llm-providers-does-hexabot-support.md).

# Which AI / LLM providers does Hexabot support?

Hexabot uses the **Vercel AI SDK** under the hood for its AI-powered actions. This means Hexabot can work with the AI model providers supported by the Vercel AI SDK, as long as the corresponding provider package and credentials are configured in your project.

You can use AI providers with actions such as:

* **AI Agent** (`ai_agent`)
* **AI Generate Reply** (`ai_generate_reply`)
* **AI Infer Object** (`ai_infer_object`)

These actions allow you to attach a **model binding** to the action step. From the model binding panel, you can select the AI provider from the **Provider** dropdown, enter the model name, and configure the required credentials.

### Supported providers

Hexabot currently supports the following Vercel AI SDK-compatible providers:

| Provider             | Provider key        |
| -------------------- | ------------------- |
| Alibaba              | `alibaba`           |
| Amazon Bedrock       | `amazon-bedrock`    |
| Anthropic            | `anthropic`         |
| AssemblyAI           | `assemblyai`        |
| Azure                | `azure`             |
| Baseten              | `baseten`           |
| Black Forest Labs    | `black-forest-labs` |
| ByteDance            | `bytedance`         |
| Cerebras             | `cerebras`          |
| Claude               | `claude`            |
| Cohere               | `cohere`            |
| Deepgram             | `deepgram`          |
| DeepInfra            | `deepinfra`         |
| DeepSeek             | `deepseek`          |
| ElevenLabs           | `elevenlabs`        |
| Fal                  | `fal`               |
| Fireworks            | `fireworks`         |
| Gateway              | `gateway`           |
| Gemini               | `gemini`            |
| Gladia               | `gladia`            |
| Google               | `google`            |
| Google Vertex AI     | `google-vertex`     |
| Groq                 | `groq`              |
| Hugging Face         | `huggingface`       |
| Hume                 | `hume`              |
| Kling AI             | `klingai`           |
| LiteLLM              | `litellm`           |
| LMNT                 | `lmnt`              |
| Luma                 | `luma`              |
| Mistral              | `mistral`           |
| Moonshot AI          | `moonshotai`        |
| OpenAI Responses API | `open-responses`    |
| OpenAI               | `openai`            |
| OpenAI-compatible    | `openai-compatible` |
| Perplexity           | `perplexity`        |
| Prodia               | `prodia`            |
| Replicate            | `replicate`         |
| Rev AI               | `revai`             |
| Together AI          | `togetherai`        |
| Vercel               | `vercel`            |
| xAI                  | `xai`               |

This includes popular LLM providers such as **OpenAI**, **Anthropic**, **Google Gemini**, **Groq**, **Mistral**, **Amazon Bedrock**, **Azure**, **Cohere**, **DeepSeek**, **Perplexity**, **xAI**, and others.

It also includes providers for additional AI capabilities, such as speech, audio, image, or multimodal services, depending on what is supported by the underlying Vercel AI SDK provider.

### How to select a provider in Hexabot

To use an AI provider in a workflow:

1. Open a flow in the visual editor.
2. Add or select an AI action, such as **AI Agent**, **AI Generate Reply**, or **AI Infer Object**.
3. Attach a **model binding** to the action step.
4. In the **Add Model binding** panel, select the provider from the **Provider** dropdown.
5. Enter the model name.
6. Select or create the required credential.
7. Save the model binding.

For example, depending on the provider you selected, you may use model names such as:

| Provider        | Example model name         |
| --------------- | -------------------------- |
| OpenAI          | `gpt-5.2`                  |
| Anthropic       | `claude-3-5-sonnet-latest` |
| Google / Gemini | `gemini-2.0-flash`         |
| Mistral         | `mistral-large-latest`     |
| Groq            | `llama-3.3-70b-versatile`  |

The exact model name depends on the provider and the models available in your account.

### Providers installed by default

When creating a new Hexabot project using the starter template, a few AI SDK provider packages are already included by default.

| Package                  | Provider        |
| ------------------------ | --------------- |
| `@ai-sdk/anthropic`      | Anthropic       |
| `@ai-sdk/amazon-bedrock` | Amazon Bedrock  |
| `@ai-sdk/google`         | Google / Gemini |
| `@ai-sdk/groq`           | Groq            |
| `@ai-sdk/mistral`        | Mistral         |

This means that, out of the box, the starter project includes support for providers such as **Anthropic**, **Amazon Bedrock**, **Google / Gemini**, **Groq**, and **Mistral**.

### Using another provider

If you want to use a provider that is not installed by default, you may need to install the corresponding `@ai-sdk/*` package in your Hexabot project.

For example, to use Mistral, you may need to install:

```bash
npm install @ai-sdk/mistral
```

For another provider, install the package recommended by the Vercel AI SDK documentation:

```bash
npm install @ai-sdk/provider-name
```

After installing the package, rebuild and restart your Hexabot project so the provider can be loaded correctly.

### Credentials

Most AI providers require credentials such as an API key, access token, or cloud configuration.

In Hexabot, credentials are managed separately from the workflow logic. When creating a model binding, you can select an existing credential or add a new one from the model binding panel.

The exact credential fields depend on the selected provider. For example:

| Provider          | Typical credential requirements                |
| ----------------- | ---------------------------------------------- |
| OpenAI            | API key                                        |
| Anthropic         | API key                                        |
| Google / Gemini   | Google AI API key                              |
| Amazon Bedrock    | AWS credentials and region                     |
| Azure             | Azure OpenAI endpoint, deployment, and API key |
| OpenAI-compatible | Base URL, API key, and model name              |

### OpenAI-compatible providers

Hexabot also supports the `openai-compatible` provider option.

This is useful when working with platforms that expose an OpenAI-compatible API, including self-hosted models, third-party model gateways, or custom inference endpoints.

In that case, you typically need to configure:

| Setting    | Description                                     |
| ---------- | ----------------------------------------------- |
| Base URL   | The API endpoint exposed by the provider        |
| API key    | The authentication key required by the provider |
| Model name | The model identifier expected by the provider   |

### Notes and limitations

Provider availability depends on both Hexabot and the installed Vercel AI SDK provider packages in your project.

Some providers may require additional configuration, environment variables, or cloud permissions.

Some providers support text generation only, while others may support embeddings, speech, transcription, image generation, or multimodal capabilities. The features available inside Hexabot depend on the selected AI action and the capabilities exposed by the underlying provider.

### Summary

Hexabot supports a wide range of AI and LLM providers through the Vercel AI SDK. You can choose the provider directly from the model binding panel when configuring AI actions such as **AI Agent**, **AI Generate Reply**, or **AI Infer Object**.

The starter template includes several providers by default, and additional providers can usually be enabled by installing the corresponding `@ai-sdk/*` package and configuring the required credentials.


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