> ## Documentation Index
> Fetch the complete documentation index at: https://docs.guild.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Meta

> Use Muse and Llama models from Meta in your Guild agents: supported models, inference providers, setup, and agent code.

Guild supports Muse and Llama models from Meta. This page lists the models Guild recognizes, the inference providers that serve them, and how to call them from an agent.

| | |
| - | - |
| Name under **Models** in the credential form | Meta |
| `provider` in `llmPreferences` | `"meta"` |
| Default model | `muse-spark-1.1` |
| Managed access | Yes, when Guild holds a managed key |

## Inference providers

You can reach these models through the Meta API itself or through a third-party provider.

| Provider | Notes |
| - | - |
| Meta | The Meta API. Available on every account. It speaks the OpenAI Chat Completions format. |
| [OpenRouter](/platform/providers/openrouter) | Serves Muse models under `meta/`, such as `muse-spark-1.3`, and Llama models under `meta-llama/`. |

Write the canonical model name, such as `muse-spark-1.1`, everywhere in Guild. Guild maps it to each provider's own model ID.

## Models

Guild prices and recognizes these Meta model IDs. A policy or preference can also name any other model your credential can reach. Third-party providers route more models than this list, and their catalogs change; see each provider's page for what it serves.

| Model | Notes |
| - | - |
| `muse-spark-1.2` | |
| `muse-spark-1.1` | The default. |

## Set up Meta

On a managed account, agents can use Meta models without a credential, as long as Guild holds a managed key for Meta. To use your own Meta account instead, add a credential. Adding your first credential switches the whole account to bring your own key (BYOK).

<Steps>
  <Step title="Open Models & providers">Click **Access & setup** in the left nav, then **Models & providers**. In an organization, only admins can open it.</Step>
  <Step title="Add a credential">Click **Add API key** and choose an inference provider from the table above.</Step>
  <Step title="Enter the provider's secret">Give the credential a **Name** and paste your provider's **API key**. [AWS Bedrock](/platform/providers/aws-bedrock) asks for an IAM role and region instead.</Step>
  <Step title="Choose Meta">Under **Models**, check **Meta**. Keep `muse-spark-1.1` as its default model or enter another from the list above. Then click **Add Key**.</Step>
</Steps>

To control which workspaces and agents can use Meta models, add a [model policy](/platform/llm-settings#model-policies) for the credential. For example, `--models "muse-*"` limits a policy to matching models:

```bash theme={null}
guild llm policy create --credential <credential-id> --publisher META --target-id <workspace-or-agent-id> --models "muse-*"
```

## Use it from an agent

Agent code never names a credential. Guild resolves the call against the workspace owner's settings. To ask for Meta explicitly, put it in `llmPreferences`:

```typescript theme={null}
const result = await task.llm.generateText({
  prompt: "Summarize this text...",
  llmPreferences: [
    { provider: "meta", model: "muse-spark-1.2" },
    { provider: "meta" },
  ],
})
```

The first entry asks for `muse-spark-1.2`. The second falls back to the default model of the matching policy. Preferences are strict: if no credential or policy allows any of them, the call fails rather than using another publisher. See [LLM preferences](/guide/llms#llm-preferences).

## Notes

* Guild reaches the Meta API through its [unified LLM proxy](/guide/llms#unified-llm-proxy). There is no raw passthrough route for Meta, unlike Anthropic and OpenAI.

## Related pages

* [Models & providers](/platform/llm-settings) for credentials, model policies, and the daily token limit
* [LLMs](/guide/llms) for `task.llm` and the unified LLM proxy
* [Usage](/insights/usage) for spend by model