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AQwen3 235B A22B Thinking 2507OPEN

Qwen3-235B-A22B-Thinking-2507 is a high-performance, open-weight Mixture-of-Experts (MoE) language model optimized for complex reasoning tasks.

128KContext window · tokens
$0.45Input price · per M tokens
$3.5Output price · per M tokens
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Benchmarks & performance

Independent benchmark scores for Qwen3 235B A22B Thinking 2507, measured by Artificial Analysis. Higher is better. Measurement mode: Reasoning.

Coding index22.1
Math index91
GPQA79%
MMLU-Pro84.3%
Humanity's Last Exam15.9%
Long Context Reasoning72%
LiveCodeBench78.8%
SciCode41.4%
MATH-50098.4%
AIME94%
AIME 202591%
IFBench51.2%
τ²-Bench53.2%
τ-Bench Banking7.8%
Terminal-Bench12%
Terminal-Bench Hard13.6%
💰 Blended price$0.747 / 1M tokens
Benchmark data by Artificial Analysis

About this model

Qwen3 235B A22B Thinking 2507 is an open-weight AI model by Alibaba. You can download and self-host it for free; the prices below are hosted-API list prices, tracked daily, for when you prefer convenience over self-hosting.

Frequently asked questions

What is Qwen3 235B A22B Thinking 2507?

Qwen3 235B A22B Thinking 2507 is an AI language model from Alibaba. It is open-weight: you can download it and run it on your own hardware, for free.

Is Qwen3 235B A22B Thinking 2507 free?

The weights are free and open — you can self-host Qwen3 235B A22B Thinking 2507 and pay nothing per token. If you prefer a hosted API, list prices are $0.45 per million input tokens and $3.5 per million output tokens.

What is Qwen3 235B A22B Thinking 2507 good at?

Independent benchmarks from Artificial Analysis give it GPQA 79%, MMLU-Pro 84.3%, Humanity's Last Exam 15.9%, Long Context Reasoning 72%, LiveCodeBench 78.8%, SciCode 41.4%, MATH-500 98.4%, AIME 94%, AIME 2025 91%, IFBench 51.2%, τ²-Bench 53.2%, τ-Bench Banking 7.8%, Terminal-Bench 12%, Terminal-Bench Hard 13.6%. It is particularly used for code generation.

Can I self-host Qwen3 235B A22B Thinking 2507?

Yes. Qwen3 235B A22B Thinking 2507 has open weights, so you can download it and run it on your own GPU or server with tools like Ollama, vLLM or llama.cpp — with no per-token cost.

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