> For the complete documentation index, see [llms.txt](https://docs.mozilla.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.mozilla.ai/any-guardrail/api-reference/index/content-safety/llama-guard.md).

# Llama Guard

Decoder-LLM safety classifier judging prompts and responses against the 14-category MLCommons hazard taxonomy.

Llama Guard is Meta's instruction-tuned safety model. Each call wraps a user prompt (and, optionally, an assistant response) in the model's moderation template listing the 14 MLCommons hazard categories (`S1` Violent Crimes ... `S14` Code Interpreter Abuse), then generates a verdict: `safe`, or `unsafe` followed by the violated category codes. This wrapper covers Llama Guard 3 (1B / 8B, text-only), evaluating the conversation as-is without an appended assistant prefix. Llama Guard 3 is trained for multilingual moderation across eight languages (English, French, German, Hindi, Italian, Portuguese, Spanish, Thai).

`meta-llama/Llama-Guard-4-12B` is deliberately not supported: it is a natively multimodal `llama4` checkpoint whose image-processing stack (`pillow` + `torchvision`) is not part of any declared extra, and its multimodal path is not reachable through this guardrail's text-only `validate()` anyway.

Verdict mapping onto `GuardrailOutput`:

* `valid` is `False` when the generation contains `unsafe` (case-insensitive), `True` otherwise.
* `categories` lists the violated hazard codes parsed from the generation, one `CategoryResult` per code (`name` = `Sx`, `description` = the taxonomy label, `triggered=True`), deduplicated in order of first appearance; empty when the verdict is `safe`. Unknown codes are kept with `description=None` so taxonomy additions still surface.
* `explanation` is the raw generated text.
* `usage` carries the prompt / completion token counts.
* No canonical `score` and no `spans` are produced (`score` is `None`).

Expected inputs: a single `input_text` string (the user prompt) plus an optional `output_text` string (an assistant response). When `output_text` is supplied, the model judges the full `[user, assistant]` turn — i.e. it moderates the response in the context of the prompt. Single strings only; list / batch input is not supported.

The models are gated on HuggingFace and distributed under Meta's Llama Community License.

For more information, see:

* [Llama Guard 3 model card (Meta)](https://www.llama.com/docs/model-cards-and-prompt-formats/llama-guard-3/)
* [meta-llama/Llama-Guard-3-1B](https://huggingface.co/meta-llama/Llama-Guard-3-1B)
* [meta-llama/Llama-Guard-3-8B](https://huggingface.co/meta-llama/Llama-Guard-3-8B)

## Supported Models

* `meta-llama/Llama-Guard-3-1B`
* `meta-llama/Llama-Guard-3-8B`

## Constructor

| Parameter  | Type                                                 | Required | Default | Description                                                                                                                                                                                                                                                                                            |
| ---------- | ---------------------------------------------------- | -------- | ------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `model_id` | \`str                                                | None\`   | No      | `None`                                                                                                                                                                                                                                                                                                 |
| `provider` | `Optional[Provider[dict[str, Any], dict[str, Any]]]` | No       | `None`  | Optional pre-configured provider. When `None`, a `HuggingFaceProvider` is built targeting `AutoModelForCausalLM` / `AutoTokenizer`. A supplied `HuggingFaceProvider` is corrected to the same classes at load time (without mutating it); any other provider (e.g. `LlamafileProvider`) is used as-is. |

Initialize the Llama Guard guardrail.

## validate

Default validation pipeline: preprocess -> inference -> postprocess.

**Parameters**

| Parameter    | Type  | Required     | Default | Description |
| ------------ | ----- | ------------ | ------- | ----------- |
| `input_text` | \`str | list\[str]\` | Yes     | —           |

**Returns:** `GuardrailOutput | list[GuardrailOutput]`

## Benchmarks

### Content Safety

| Dataset (rev)                    | Metric | Threshold    | Value    | Harness                 | Source                           | Contam. |
| -------------------------------- | ------ | ------------ | -------- | ----------------------- | -------------------------------- | ------- |
| openai\_moderation (unspecified) | f1     | native-valid | 0.840816 | guardrail-bench+ag0.7.4 | measured:guardrail-bench+ag0.7.4 |         |
| xstest (unspecified)             | fpr    | native-valid | 0.028    | guardrail-bench+ag0.7.4 | measured:guardrail-bench+ag0.7.4 |         |
| wildguardmix (unspecified)       | f1     | native-valid | 0.83004  | guardrail-bench+ag0.7.4 | measured:guardrail-bench+ag0.7.4 |         |
| aegis (unspecified)              | f1     | native-valid | 0.76494  | guardrail-bench+ag0.7.4 | measured:guardrail-bench+ag0.7.4 |         |
| jbb (unspecified)                | f1     | native-valid | 0.890909 | guardrail-bench+ag0.7.4 | measured:guardrail-bench+ag0.7.4 |         |
| orbench (unspecified)            | fpr    | native-valid | 0.126316 | guardrail-bench+ag0.7.4 | measured:guardrail-bench+ag0.7.4 |         |

## License

* **Vendor:** Meta
* **Default license:** `llama-3.2` (of the default model/service)

| Model variant                 | License     |
| ----------------------------- | ----------- |
| `meta-llama/Llama-Guard-3-1B` | `llama-3.2` |
| `meta-llama/Llama-Guard-3-8B` | `llama-3.1` |


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