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Qwen3.8 27BOPEN
Qwen3.8 27B is an open-weight dense vision-language model from Qwen.
Prices update automatically — checked daily against provider list prices.
- $0.37 per 1M tokens, assuming 3 input for 1 output the convention used by Artificial Analysis
- cheaper than 46% of the 202 open-weight models tracked here
- 18 of 43 Alibaba models tracked here, from cheapest
Benchmarks & performance
Independent benchmark scores for Qwen3.8 27B, measured by Artificial Analysis. Higher is better. Measurement mode: Xhigh.
For the same budget, Qwen3.8 27B delivers 4.2 times more capability. Open weights also mean you can self-host it and pay nothing per token.
Models at this level cost $1.69 per 1M tokens (median of 9) — this one costs $0.37.
Cheaper and better on this index: DeepSeek V4.1 Flash 1017 · Claude Haiku 5.5 · Claude Haiku 5.5 (batch) and 11 more
About this model
Qwen3.8 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 Qwen3.8 27B?
Qwen3.8 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 33.7 on the Artificial Analysis intelligence index.
Is Qwen3.8 27B free?
The weights are free and open — you can self-host Qwen3.8 27B and pay nothing per token. If you prefer a hosted API, list prices are $0.04 per million input tokens and $1.35 per million output tokens.
What is Qwen3.8 27B good at?
Independent benchmarks from Artificial Analysis give it GPQA 90.5%, Humanity's Last Exam 33.9%, Long Context Reasoning 82%, SciCode 46.6%, τ-Bench Banking 48%, Terminal-Bench 79.8%. It is particularly used for code generation.
How fast is Qwen3.8 27B?
It generates about 38.5 tokens per second, with a median 1.45s delay before the first token. Measured independently by Artificial Analysis.
Can I self-host Qwen3.8 27B?
Yes. Qwen3.8 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.