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Qwen3.6 PlusOPEN
Qwen 3.6 Plus builds on a hybrid architecture that combines efficient linear attention with sparse mixture-of-experts routing, enabling strong scalability and high-performance inference.
Prices update automatically — checked daily against provider list prices.
- $0.74 per 1M tokens, assuming 3 input for 1 output the convention used by Artificial Analysis
- cheaper than 26% of the 191 open-weight models tracked here
- 35 of 51 Alibaba models tracked here, from cheapest
Benchmarks & performance
Independent benchmark scores for Qwen3.6 Plus, measured by Artificial Analysis. Higher is better.
For the same budget, Qwen3.6 Plus delivers 5.7 times more capability. Open weights also mean you can self-host it and pay nothing per token.
Models at this level cost $0.93 per 1M tokens (median of 21) — this one costs $0.74.
Cheaper and better on this index: GLM 5.3 Flash · Gemini 3.7 Flash (batch) · GPT-5.6 Luna and 10 more
About this model
Qwen3.6 Plus 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 Qwen3.6 Plus?
Qwen3.6 Plus 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 40.5 on the Artificial Analysis intelligence index.
Is Qwen3.6 Plus free?
The weights are free and open — you can self-host Qwen3.6 Plus and pay nothing per token. If you prefer a hosted API, list prices are $0.33 per million input tokens and $1.95 per million output tokens.
What is Qwen3.6 Plus good at?
Independent benchmarks from Artificial Analysis give it GPQA 88.2%, Humanity's Last Exam 27.8%, Long Context Reasoning 72.3%, SciCode 40.7%, IFBench 75.2%, τ²-Bench 97.7%, τ-Bench Banking 20.8%, Terminal-Bench 61.4%, Terminal-Bench Hard 43.9%. It is particularly used for code generation.
Can I self-host Qwen3.6 Plus?
Yes. Qwen3.6 Plus 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.