👉 Introduction
This is the official model card for OPD-Aha-4B, built on
Qwen/Qwen3.5-4B.
OPD-Aha is an on-policy self-distillation framework for improving fine-grained visual perception
and multimodal mathematical reasoning. It trains the model with a frozen visual teacher and a
counterfactual visual input so that learning focuses on evidence that changes the teacher
distribution.
⚡ Serving
The project provides a vLLM serving entrypoint:
git clone https://github.com/Echochef/OPD-Aha.git
cd OPD-Aha
MODEL_PATH=CewEhao/OPD-Aha-4B \
SERVED_MODEL_NAME=opd-aha-4b \
bash scripts/serve_model.sh
🏋️ Training and evaluation
Training, checkpoint merging, inference, and evaluation code is available in
Echochef/OPD-Aha. The repository includes fine-grained
perception evaluation for V*Bench, HR-Bench, MME-RealWorld, and ZoomBench, together with
mathematical reasoning evaluation for MathVista, MathVerse, WeMath, MathVision, and DynaMath.
🙏 Acknowledgements
OPD-Aha builds on Qwen,
verl,
vLLM, and
Vision-OPD.
📄 License
This model is released under the Apache-2.0 License. The base model and datasets remain subject to
their respective licenses.