> 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/qwen3-guard-stream.md).

# Qwen3Guard-Stream

Token-level streaming safety moderation with span output.

Classifier heads on a Qwen3 backbone (loaded as remote code) that judge the user prompt as a whole and every assistant response token individually, each with a three-level severity (`Safe` / `Controversial` / `Unsafe`, where `Controversial` means harmfulness is context-dependent). The model is multilingual (the Qwen3Guard series covers up to 119 languages) and released under Apache-2.0. `validate` is a non-streaming facade over the token-level streaming API: it feeds the whole prompt, then each `output_text` token in turn, and aggregates the worst severity seen.

Verdict mapping onto `GuardrailOutput`:

* `valid` is `True` only when everything judged is `Safe`; when `strict=False`, `Controversial` content also passes (only `Unsafe` fails).
* `score` maps the worst severity onto the canonical risk axis (higher = riskier): `Safe` → `0.0`, `Controversial` → `0.5`, `Unsafe` → `1.0`.
* `categories` lists the distinct violation categories (`triggered=True`) seen across the prompt and non-`Safe` response tokens.
* `spans` (response mode only) merges consecutive flagged response tokens into character-offset runs over `output_text`, each labeled with its category and severity-derived `score`; `None` when nothing is flagged or the tokenizer cannot supply offsets (a slow tokenizer degrades spans gracefully).
* `extra` carries the worst `severity`, the `prompt_severity`, and (in response mode) the `response_severity`.
* Fails closed (`valid=False` with `extra={"parse_failure": True}`) when the backend reports no usable risk level.

For the generative variants (`Qwen3Guard-Gen-*`), see `Qwen3Guard`.

Expected inputs: a single `input_text` (the user prompt; required) plus an optional `output_text` (the assistant response). With no `output_text` only the prompt is moderated and no spans are produced. List/batch input is not supported — passing a list raises `TypeError`.

HuggingFace-only: the model ships its classification heads as remote code, so a user-supplied provider must be a `HuggingFaceProvider` constructed with `trust_remote_code=True`. The remote modeling code currently requires `transformers>=4.51,<5` (transformers 5 removed APIs it relies on); construction raises `ImportError` on transformers >= 5.

For more information, see:

* [Qwen3Guard-Stream-0.6B model card](https://huggingface.co/Qwen/Qwen3Guard-Stream-0.6B) (default).
* [Qwen3Guard-Stream-4B model card](https://huggingface.co/Qwen/Qwen3Guard-Stream-4B).
* [Qwen3Guard-Stream-8B model card](https://huggingface.co/Qwen/Qwen3Guard-Stream-8B).
* [Qwen3Guard Technical Report (arXiv:2510.14276)](https://arxiv.org/abs/2510.14276)
* [Qwen3Guard: Real-time Safety for Your Token Stream (Qwen blog)](https://qwenlm.github.io/blog/qwen3guard/)

## Supported Models

* `Qwen/Qwen3Guard-Stream-0.6B`
* `Qwen/Qwen3Guard-Stream-4B`
* `Qwen/Qwen3Guard-Stream-8B`

## Constructor

| Parameter  | Type                                                 | Required | Default | Description                                                                                                                                                                                                                                                                             |
| ---------- | ---------------------------------------------------- | -------- | ------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `strict`   | `bool`                                               | No       | `True`  | If `True` (default), only `Safe` verdicts pass validation; set `False` to let `Controversial` content pass (`valid=True`), leaving it reflected only in `score`, `extra`, and `spans`.                                                                                                  |
| `model_id` | \`str                                                | None\`   | No      | `None`                                                                                                                                                                                                                                                                                  |
| `provider` | `Optional[Provider[dict[str, Any], dict[str, Any]]]` | No       | `None`  | Optional pre-configured provider. Must be a `HuggingFaceProvider` constructed with `trust_remote_code=True` (the classification heads load as remote code); it is loaded with `model_class=AutoModel` / `tokenizer_class=AutoTokenizer`. Defaults to one loading the remote-code model. |

Initialize the Qwen3GuardStream guardrail.

## validate

Moderate a user prompt and, optionally, the assistant response to it.

**Parameters**

| Parameter     | Type  | Required | Default | Description                                                                                                                  |
| ------------- | ----- | -------- | ------- | ---------------------------------------------------------------------------------------------------------------------------- |
| `input_text`  | `str` | Yes      | —       | The user prompt to moderate, e.g. `"How do I make a bomb?"`. A single string; list/batch input is rejected with `TypeError`. |
| `output_text` | \`str | None\`   | No      | `None`                                                                                                                       |

**Returns:** `GuardrailOutput`

## Benchmarks

No benchmark results recorded yet. See the [benchmark methodology](/any-guardrail/api-reference/benchmarks.md) for how numbers are harvested (published) or measured and added.

## License

* **Vendor:** Qwen
* **Default license:** `apache-2.0` (of the default model/service)


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