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AQwen3 Max ThinkingOPEN

Qwen3-Max-Thinking is the flagship reasoning model in the Qwen3 series, designed for high-stakes cognitive tasks that require deep, multi-step reasoning.

262KContext window · tokens
$0.78Input price · per M tokens
$3.9Output price · per M tokens
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Prices update automatically — checked daily against provider list prices.

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Benchmarks & performance

Independent benchmark scores for Qwen3 Max Thinking, measured by Artificial Analysis. Higher is better.

Intelligence index32.5
GPQA86.1%
Humanity's Last Exam28%
Long Context Reasoning70.3%
SciCode43.1%
IFBench70.7%
τ²-Bench83.6%
Terminal-Bench Hard24.2%
vs. models measured heretop 44%
Scores higher than 56% of the 273 models measured by Artificial Analysis and tracked here.
Models at this level cost $0.72 per 1M tokens (median of 22) — this one costs $1.56.
Cheaper and better on this index: GLM 5.3 Flash · Gemini 3.7 Flash · Gemini 3.7 Flash (batch) and 42 more
Benchmark data by Artificial Analysis

About this model

Qwen3 Max Thinking 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 Max Thinking?

Qwen3 Max Thinking is an AI language model from Alibaba. It is open-weight: you can download it and run it on your own hardware, for free. It scores 32.5 on the Artificial Analysis intelligence index.

Is Qwen3 Max Thinking free?

The weights are free and open — you can self-host Qwen3 Max Thinking and pay nothing per token. If you prefer a hosted API, list prices are $0.78 per million input tokens and $3.9 per million output tokens.

What is Qwen3 Max Thinking good at?

Independent benchmarks from Artificial Analysis give it GPQA 86.1%, Humanity's Last Exam 28%, Long Context Reasoning 70.3%, SciCode 43.1%, IFBench 70.7%, τ²-Bench 83.6%, Terminal-Bench Hard 24.2%.

Can I self-host Qwen3 Max Thinking?

Yes. Qwen3 Max Thinking 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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