QwenQwen3 235B A22B Instruct 2507
Qwen's Qwen3 235B A22B Instruct 2507 is a chat model capable of streaming, web search, code execution, function calling, and structured output. It is genuinely best at handling complex mathematical problems, as evidenced by its top 25% score on the MATH-500 benchmark.
Input
Output
Context
262K
Max Output
16K
Parameters
235.1B
Technical Specifications
Input Modalities
Output Modalities
Capabilities
Loading capabilities…
Benchmarks
Resources & Links
Estimated GPU requirements for Qwen3 235B A22B Instruct 2507
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 Qwen3 235B A22B Instruct 2507
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Qwen3 235B A22B Instruct 2507 advertises a context window of 262,144 tokens, with a maximum output of 16,384 tokens in a single response. The figure is the creator's published maximum; a given provider may serve less, and the gateway routes on what each provider actually serves.
Yes. Qwen3 235B A22B Instruct 2507 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.
Qwen3 235B A22B Instruct 2507 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.
Qwen3 235B A22B Instruct 2507 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 Qwen3 235B A22B Instruct 2507 is shown as not available rather than estimated.
Not on the managed pool today; Qwen3 235B A22B Instruct 2507 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 231.4 GB at INT8 for the weights and a default context, from the catalog's 235.1B 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, provider APIs and benchmark publishers, each tagged with its source.
Last updated: Nov 6, 2026
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