Qwen 3 0.6B FP8
Qwen builds Qwen 3 0.6B FP 8, a chat model that excels at reasoning, instruction-following, and multilingual support, with capabilities including function calling, JSON mode, and text generation. Its architecture features a context window of 40,960 tokens and a mixture-of-experts (MoE) design, allowing for seamless switching between thinking and non-thinking modes.
Input
Output
Context
41K
Max Output
33K
Parameters
751.7M
Technical Specifications
Input Modalities
Output Modalities
Capabilities
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Benchmarks
Resources & Links
Estimated GPU requirements for Qwen 3 0.6B FP8
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 3 0.6B FP8
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Qwen 3 0.6B FP8 advertises a context window of 40,960 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 3 0.6B FP8 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 3 0.6B FP8 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.
Qwen 3 0.6B FP8 has published results from Artificial Analysis, shown by suite in the benchmarks card above exactly as the publisher reported them. Scores are not combined across suites, and a suite that has not measured Qwen 3 0.6B FP8 is shown as not available rather than estimated.
Not on the managed pool today; Qwen 3 0.6B FP8 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 1.2 GB at INT8 for the weights and a default context, from the catalog's 751.7M 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: Sep 13, 2026
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