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Qwen3.5-27BOPEN
The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance.
Prices update automatically — checked daily against provider list prices.
- $0.54 per 1M tokens, assuming 3 input for 1 output the convention used by Artificial Analysis
- cheaper than 35% of the 191 open-weight models tracked here
- 28 of 51 Alibaba models tracked here, from cheapest
Benchmarks & performance
Independent benchmark scores for Qwen3.5-27B, measured by Artificial Analysis. Higher is better. Measurement mode: Reasoning.
For the same budget, Qwen3.5-27B delivers 6.7 times more capability. Open weights also mean you can self-host it and pay nothing per token.
Models at this level cost $1.72 per 1M tokens (median of 20) — this one costs $0.54.
Cheaper and better on this index: GLM 5.3 Flash · Gemini 3.7 Flash (batch) · GPT-5.6 Luna and 14 more
About this model
Qwen3.5-27B 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 Qwen3.5-27B?
Qwen3.5-27B 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 34.6 on the Artificial Analysis intelligence index.
Is Qwen3.5-27B free?
The weights are free and open — you can self-host Qwen3.5-27B and pay nothing per token. If you prefer a hosted API, list prices are $0.2 per million input tokens and $1.56 per million output tokens.
What is Qwen3.5-27B good at?
Independent benchmarks from Artificial Analysis give it GPQA 85.8%, Humanity's Last Exam 23.9%, Long Context Reasoning 72.3%, SciCode 39.5%, IFBench 75.6%, τ²-Bench 93.9%, Terminal-Bench Hard 32.6%.
Can I self-host Qwen3.5-27B?
Yes. Qwen3.5-27B 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.