MODEL PROFILE

Qwen3Guard-Stream-0.6B

阿里巴巴 · Qwen · Qwen3Guard-Stream-0.6B

**Qwen3Guard** is a series of safety moderation models built upon Qwen3 and trained on a dataset of 1.19 million prompts and responses labeled for safety. The series includes models of three sizes (0.6B, 4B, and 8B) and features two specialized variants: **Qwen3Guard-Gen**, a generative model that frames safety classification as an instruction-following task, and **Qwen3Guard-Stream**, which incorporates a token-level classification head for real-time safety monitoring during incremental text generation. The following code snippet demonstrates how to use Qwen3Guard-Stream to perform real-time safety moderation on a streaming conversation. > [!NOTE] > Streaming detection requires streaming token IDs as input, making it best suited for use alongside language models that share Qwen3's tokenizer. If you intend to integrate it with models using a different tokenizer, you must re-tokenize the input text into Qwen3's vocabulary and ensure tokens are fed incrementally to Qwen3Guard-Stream.

Embeddings & similaritylicense:apache-2.0
Context windowNot disclosed
Input → OutputText → Embedding
Model weightsNot verified
Profile updated2026/10/31 04:17:36
OVERVIEW

Model overview

**Qwen3Guard** is a series of safety moderation models built upon Qwen3 and trained on a dataset of 1.19 million prompts and responses labeled for safety. The series includes models of three sizes (0.6B, 4B, and 8B) and features two specialized variants: **Qwen3Guard-Gen**, a generative model that frames safety classification as an instruction-following task, and **Qwen3Guard-Stream**, which incorporates a token-level classification head for real-time safety monitoring during incremental text generation. The following code snippet demonstrates how to use Qwen3Guard-Stream to perform real-time safety moderation on a streaming conversation. > [!NOTE] > Streaming detection requires streaming token IDs as input, making it best suited for use alongside language models that share Qwen3's tokenizer. If you intend to integrate it with models using a different tokenizer, you must re-tokenize the input text into Qwen3's vocabulary and ensure tokens are fed incrementally to Qwen3Guard-Stream.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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Frequently asked questions

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Sources & traceability

许可证:apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。