Qwen: Qwen3.5-Flash

qwen/qwen3.5-flash-02-23

Released Feb 25, 20261,000,000 context

$0.10/M input tokens$0.40/M output tokens

The Qwen3.5 native vision-language Flash models are built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. Compared to the 3 series, these models deliver a leap forward in performance for both pure text and multimodal tasks, offering fast response times while balancing inference speed and overall performance.

Qwen: Qwen3.5-Flash

qwen/qwen3.5-flash-02-23

Released Feb 25, 20261,000,000 context

$0.10/M input tokens$0.40/M output tokens

The Qwen3.5 native vision-language Flash models are built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. Compared to the 3 series, these models deliver a leap forward in performance for both pure text and multimodal tasks, offering fast response times while balancing inference speed and overall performance.

Recent activity on Qwen3.5-Flash

Total usage per day on OpenRouter

Prompt

38.7M

Reasoning

13.7M

Completion

961K

Prompt tokens measure input size. Reasoning tokens show internal thinking before a response. Completion tokens reflect total output length.