Qwen2.5-VL Deployment Architecture and Hardware Adaptation Solution
Qwen2.5-VL provides four parameter scale model versions to meet the deployment needs of different scenarios:
downsizedVersion 3BRequires a GPU with at least 8GB of video memory, suitable for developers prototyping on a local computer. Intermediate scaleVersion 7BDemand increases to 16GB of video memory, which is the limit for current consumer graphics cards (e.g. RTX 4090).
And the professional-gradeVersions 32B and 72BThen you need a high-end computing card (such as NVIDIA A100) with more than 24GB of video memory, and these two versions are more suitable for deployment in enterprise servers or cloud environments. It should be noted that the 72B version is recommended for use with distributed computing frameworks.
The technical team provides a complete deployment tool chain:
- Support for PyTorch CUDA acceleration
- Integration with vLLM high-performance inference framework (version > 0.7.2)
- Optional Flash Attention2 Optimization Solution
- Provide Web Demo deployment scripts
For video processing scenarios, it is recommended to additionally install the decord codec library for best performance. windows users may need to compile this component from source.
This answer comes from the articleQwen2.5-VL: an open source multimodal grand model supporting image-video document parsingThe
