Qwen3.5 9B
Summary: Qwen3.5-9B is a compact multimodal model from Alibaba Cloud's Qwen team, built on a hybrid architecture that combines linear attention with standard attention layers and an integrated vision encoder. Despite its compact 9B parameter size, the model natively supports an extended 262k token context window, reasoning ("thinking mode"), tool calling, and multilingual understanding across 201 languages and dialects. In addition to text, it processes both image and video input, making it a fast, cost-efficient choice for conversational agents, real-time assistants, and vision-language applications.
Intelligence
Speed
Input
Output
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Medium
High
Text, Image, Video
Text
Central parameters
Description: Compact multimodal model from Alibaba Cloud with 9B parameters, combining hybrid linear attention with standard attention layers and a vision encoder for fast, efficient inference.
Model identifier: Qwen/Qwen3.5-9B
IONOS CLOUD AI Model Hub Lifecycle and Alternatives
IONOS CLOUD start date
End of Life
Alternative
Successor
July 22, 2026
N/A
Origin
Provider
Country
License
Flavor
Release
Technology
Context window
Parameters
Quantization
Multilingual
Further details
Modalities
Text
Image
Video
Audio
Input and output
Input
Input
Not supported
**Note:**The video content is provided as a URL using the video_url content type. The AI Model Hub fetches the video from the URL, so the URL must be public. You can include up to four images in a single request.
Endpoints
Chat completions
Embeddings
Image generation
v1/chat/completions
Not supported
Not supported
Features
Streaming
Reasoning
Tool calling
Supported
Supported
Supported
Reasoning example
Qwen3.5-9B operates in thinking mode by default, generating an internal reasoning trace before producing its final response. It makes the model well-suited for complex, multi-step reasoning tasks.
Unlike models that offer configurable reasoning effort levels (low, medium, high), Qwen3.5-9B does not support this granularity. Instead, reasoning is either on (default) or off. To deactivate it, set "reasoning_effort": "none".
Note: The reasoning trace counts toward max_tokens. If max_tokens is set too low, reasoning can consume the entire token budget, leaving no tokens for the final answer. Activating reasoning also increases response latency, since the model generates the reasoning trace in addition to the final answer.
Request
Response (shortened for readability)
Deactivate reasoning
To skip the internal reasoning trace and return only the final answer, set "reasoning_effort": "none".
Usage example
Chat completions
The following example demonstrates how to use Qwen3.5-9B for everyday conversational tasks, such as drafting a concise product description.
API Endpoint: POST https://openai.inference.de-txl.ionos.com/v1/chat/completions
Request:
Response:
Vision model example
Video input example
Qwen3.5-9B also accepts video input. Pass the clip with the video_url content type; the AI Model Hub fetches the file, so the URL must be public.
Stream chat completions
To receive responses in real time, you can use streaming. When streaming is selected, usage statistics are not included by default. To obtain usage information in the final stream chunk, you must explicitly set "stream_options": {"include_usage": true}.
API Endpoint: POST https://openai.inference.de-txl.ionos.com/v1/chat/completions
Request:
Response:
Rate limits
Rate limits ensure fair usage and reliable access to the AI Model Hub. In addition to the contract-wide rate limits, no model-specific limits apply.
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