Qwen3.5-Flash
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-02-23
- Context
- 1M tokens
- Completion cap
- 65,536
- Tools
- Yes
- JSON
- Yes
- Released
- 2026-02-25
Call it from Geek Hub
Same OpenAI SDK. Change the base URL and the model id.
curl https://api.geekhub.mx/v1/chat/completions \
-H "Authorization: Bearer $GEEKHUB_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen/qwen3.5-flash-02-23",
"messages": [{"role": "user", "content": "Hola"}]
}'Get an API keyFrequently asked questions
- What is Qwen3.5-Flash?
- 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. Qwen3.5-Flash runs on the Geek Hub API (OpenAI-compatible). Model id: qwen/qwen3.5-flash-02-23.
- Is Qwen3.5-Flash free?
- No. Input is $0.0709 per 1M tokens and output is $0.2834 per 1M tokens on Geek Hub (markup included).
- What is the context length of Qwen3.5-Flash?
- Qwen3.5-Flash has a 1M tokens context window. It supports up to 65,536 completion tokens.
- Does Qwen3.5-Flash support tool calling and structured outputs?
- Qwen3.5-Flash accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.
- When was Qwen3.5-Flash released?
- Qwen3.5-Flash was released on 2026-02-25.
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