Qwen 3guard Gen 0.6B
Qwen builds the Qwen 3guard Gen 0.6B, a chat model that excels at safety moderation tasks, particularly in classifying outputs into safe, controversial, and unsafe severity levels. It is notable for its multilingual support, covering 119 languages and dialects, and its use of a generative approach that frames safety classification as an instruction-following task.
Input
Output
Context
33K
Max Output
33K
Parameters
600M
Technical Specifications
Input Modalities
Output Modalities
Capabilities
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Resources & Links
Estimated GPU requirements for Qwen 3guard Gen 0.6B
Estimates based on INT8 quantization at up to 32K context. A count above one assumes tensor parallelism across the cards. Actual requirements vary by framework and configuration.
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Frequently asked questions about Qwen 3guard Gen 0.6B
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Qwen 3guard Gen 0.6B advertises a context window of 32,768 tokens, with a maximum output of 32,768 tokens in a single response. The figure is the creator's published maximum; a given host may serve less, and the gateway routes on what each host actually serves.
Yes. Qwen 3guard Gen 0.6B is an open-weight model released under the Apache 2.0 license, so the weights can be downloaded and self-hosted within that license's terms.
Qwen 3guard Gen 0.6B accepts Text and produces Text. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
No published benchmark result for Qwen 3guard Gen 0.6B is in the catalog yet, so the model is shown as unmeasured. It is not ranked or estimated; the router treats it as unknown for every task until a suite measures it.
Not on the managed pool today; Qwen 3guard Gen 0.6B is listed for reference and comparison. Connect your own provider key or endpoint that serves it and the gateway runs it on your account, with routing decisions recorded the same way.
About 1.0 GB at INT8 for the weights and a default context, from the catalog's 600M parameter count; FP16 needs roughly twice that, and long contexts or many concurrent requests add KV cache on top. The GPU section on this page lists cards that hold it, and the capacity planner sizes it for your context length and traffic.
Fields collected from public registries, host APIs and benchmark publishers, each tagged with its source.
Last updated: Aug 28, 2026
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