The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency.
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Independent benchmark scores for Qwen3.5 397B A17B, measured by Artificial Analysis. Higher is better. Measurement mode: Reasoning.
Qwen3.5 397B A17B 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.
Qwen3.5 397B A17B 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 34.3 on the Artificial Analysis intelligence index.
The weights are free and open — you can self-host Qwen3.5 397B A17B and pay nothing per token. If you prefer a hosted API, list prices are $0.39 per million input tokens and $2.34 per million output tokens.
Independent benchmarks from Artificial Analysis give it GPQA 89.3%, Humanity's Last Exam 29%, Long Context Reasoning 72.7%, SciCode 42%, IFBench 78.8%, τ²-Bench 95.6%, τ-Bench Banking 13.4%, Terminal-Bench 51.3%, Terminal-Bench Hard 40.9%. It is particularly used for code generation.
It generates about 88.8 tokens per second, with a median 1.45s delay before the first token. Measured independently by Artificial Analysis.
Yes. Qwen3.5 397B A17B 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.