Qwen 3 4B Base
Qwen 3 4B Base is a chat model developed by Qwen, exceling at text generation, reasoning, and function calling due to its comprehensive pre-training on a diverse corpus of 36 trillion tokens across 119 languages. Its notable technical trait is the three-stage pre-training process, which enhances long-context comprehension by extending training sequence lengths up to 32,768 tokens.
Input
Output
Context
33K
Max Output
33K
Parameters
4B
Technical Specifications
Input Modalities
Output Modalities
Capabilities
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Resources & Links
Estimated GPU requirements for Qwen 3 4B Base
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 4B Base
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Qwen 3 4B Base 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 3 4B Base 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 4B Base 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 3 4B Base 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 3 4B Base 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 4.3 GB at INT8 for the weights and a default context, from the catalog's 4B 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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