Qwen: Qwen3.5-Flash
Qwen3.5-Flash from Qwen offers a generous 1M token context window and multimodal support at low cost, but without benchmark data its actual performance cannot be assessed — the Flash branding suggests speed optimisation over raw capability.
Assessment date: March 14, 2026
Our methodology takes into account a range of factors including pricing, functionality, capabilities, benchmark performance, and real-world applicability. Rankings are reviewed and updated regularly as new models are released. Issues with our rankings? Contact us
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.
Capabilities
Architecture
| Modality | Text + Image + Video → Text |
| Tokenizer | Qwen3 |
Model Information
Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.10 | $0.000100 |
| Output | $0.40 | $0.000400 |
Live Performance
Live endpoint metrics — refreshed every 30 minutes.
