[This track](https://www.kaggle.com/competitions/track-2-large-model-inference-optimization)  focuses on evaluating participants' ability to optimize large model inference performance. Participants are required to perform extreme inference throughput optimization on **Qwen3-4B** while strictly maintaining model accuracy and without significantly increasing latency.

Participants must comprehensively utilize parallel strategies, memory management, compute kernels, and sampling algorithms to unlock maximum performance potential on the designated framework and hardware.

### Designated Resources:

- **Large Model Inference Framework**: vllm-plugin-FL  
  🔗 https://github.com/flagos-ai/vllm-plugin-FL
- **High-Performance Operator Library**: FlagGems  
  🔗 https://github.com/FlagOpen/FlagGems
- **Model**: Qwen3-4B