Qwen: Qwen3.5-Flash

qwen/qwen3.5-flash-02-23

Released Feb 25, 20261,000,000 context$0.065/M input tokens$0.26/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$0.065/M input tokens$0.26/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.

Sample code and API for Qwen3.5-Flash

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Using third-party SDKs

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