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Provided by OpenRouter
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.
1,000,000 tokens$0.100/M$0.400/MThe 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.
Performance may vary based on query complexity, context length, and task type. Consider using higher-tier models for production-critical applications.
This model requires credits to use. Qwen: Qwen3.5-Flash offers advanced capabilities and high-performance features for production-grade applications.
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