New Multimodal

Qwen3.5 9B

Alibaba's dense Qwen3.5 9B vision-language model with Jetson-specific checkpoints for Orin and Thor

Run on Jetson
Memory Requirement 8GB RAM
Precision NVFP4 / W4A16
Size 5GB

Jetson Inference - Supported Inference Engines

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Container 
# Run Command
sudo docker run -it --rm --pull always --runtime=nvidia --network host ghcr.io/nvidia-ai-iot/vllm:latest-jetson-orin vllm serve Kbenkhaled/Qwen3.5-9B-quantized.w4a16 --gpu-memory-utilization 0.8 --enable-prefix-caching --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder

Model Details

HuggingFace View on HuggingFace

Qwen3.5 9B is a dense vision-language model in the Qwen3.5 family aimed at stronger reasoning, visual understanding, and agentic behavior on Jetson. This entry uses a W4A16 checkpoint on Jetson Orin and an NVFP4 checkpoint on Jetson Thor.

Inputs and Outputs

Input: Text and images

Output: Text

Intended Use Cases

  • Visual reasoning: Stronger multimodal reasoning over image and text inputs
  • Image understanding: Detailed captioning, scene description, and analysis
  • Tool calling: Native Qwen tool-call parsing in vLLM
  • Agents: Local assistants and workflow automation

Additional Resources