Qwen3.5-Flashon Krater.ai
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.
Released February 25, 2026
Specifications
Qwen3.5-Flash at a glance
Context
1M tokens
Max output
65.5K tokens
Input
Text, Image, Video
Output
Text
Input price
$0.07 / 1M
Output price
$0.26 / 1M
Capabilities
What it is good at
Catalog capabilities
- Accepts image input
- Generates text responses
- Supports tool calling
- Supports structured outputs
Good for
Compare
Compare Qwen3.5-Flash
Qwen3.5-Flash vs Qwen3.5-122B-A10B
The Qwen3.5 122B-A10B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency.
Open comparisonQwen3.5-Flash vs Qwen3.5-27B
The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance.
Open comparisonQwen3.5-Flash vs Qwen3.5 397B A17B
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency.
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