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---
license: apache-2.0
---
# II-Medical-32B-Preview
![image/png](https://cdn-uploads.huggingface.co/production/uploads/63466107f7bd6326925fc770/6R3uJGH1MKGSZt9F88Gvc.png)
## I. Model Overview
II-Medical-32B-Preview is the latest advanced large language model developed by Intelligent Internet, specifically designed to enhance AI-driven medical reasoning. As our first 32B-scale model version, it significantly advances the capabilities of medical question answering.
## II. Training Methodology
We collected and generated a comprehensive set of reasoning datasets for the medical domain and performed SFT fine-tuning on the [Qwen3-32B](https://huggingface.co/Qwen/Qwen3-32B) model.
For the hyperparameter:
- Max Length: 16378.
- Batch Size: 128.
- Learning-Rate: 2e-5.
- Number Of Epoch: 4.
## III. Evaluation Results
![image/png](https://cdn-uploads.huggingface.co/production/uploads/63466107f7bd6326925fc770/nfyIuAiaBLKZ1cesLN1te.png)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/63466107f7bd6326925fc770/4S65RIgYgOk7GjtsRs0vM.png)
We evaluated on 10 medical QA benchmarks including MedMCQA, MedQA, PubMedQA, HealthBench, medical related questions from MMLU-Pro, small QA sets from Lancet and the New England
Journal of Medicine, 4 Options and 5 Options splits from the MedBullets platform and MedXpertQA.
| Model | MedMC | MedQA | PubMed | MMLU-P | HealthBench | Lancet | MedB-4 | MedB-5 | MedX | NEJM | Avg |
|--------------------------|-------|-------|--------|--------|------|--------|--------|--------|------|-------|-------|
| [HuatuoGPT-o1-72B](https://huggingface.co/FreedomIntelligence/HuatuoGPT-o1-72B) | 76.76 | 88.85 | 79.90 | 80.46 | 22.73 | 70.87 | 77.27 | 73.05 |23.53 |76.29 | 66.97 |
| [M1](https://huggingface.co/UCSC-VLAA/m1-7B-23K) | 62.54 | 75.81 | 75.80 | 65.86 | 15.51 | 62.62 | 63.64 | 59.74 |19.59 |64.34 | 56.55 |
| [Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) | 66.53 | 81.38 | 73.9 | 77.85 | 42.27 | 66.26 | 68.83 | 62.66 |19.59 |69.65 | 62.89 |
| [Qwen3-32B](https://huggingface.co/Qwen/Qwen3-32B) | 74.18 | 88.92 | 76.1 | 80.7 | 47.08 | 72.33 | 72.27 | 71.42 |28.04 |76.94 | 68.80 |
| [MedGemma-27B-IT](https://huggingface.co/google/medgemma-27b-text-it) | 73.24 | 87.27 | 70.9 | 80.13 | 46.54| 70.14 | 75.32 | 73.37 |25.55 |76.28 | 67.87 |
| [II-Medical-8B](https://huggingface.co/Intelligent-Internet/II-Medical-8B) | 71.57 | 87.90 | 78.7 |80.46 | 40.02| 70.38 | 78.25 | 72.07 |25.26 |73.13 |67.77 |
| [II-Medical-8B-1706](https://huggingface.co/Intelligent-Internet/II-Medical-8B-1706) | 74.44 | 88.61 | 79.8 | 81.04 | 46.8 | 71.60 | 80.84 | 74.67 |29.63 |77.61 | 70.47 |
| [II-Medical-32B-Preview](https://huggingface.co/Intelligent-Internet/II-Medical-32B-Preview) | 75.16 | 90.02 | 79.1 | 80.71 | 47.24 | 75.48 | 81.16 | 74.68 |31.42 | 80.43 | **71.54** |
## IV. Dataset Release
More importantly, besides the II-Medical-32B-Preview, we also release the training datasets of our SFT/Preview II-Medical and also our RL dataset.
- [II-Medical-Reasoning-SFT](https://huggingface.co/datasets/Intelligent-Internet/II-Medical-Reasoning-SFT)
- [II-Medical-RL-MedReason](https://huggingface.co/datasets/Intelligent-Internet/II-Medical-RL)
- [II-Medical-RL-ChatDoctor](https://huggingface.co/datasets/Intelligent-Internet/ChatDoctor-RL)
We believe this work will be valuable resource for the community and contributes to the advancement of medical reasoning capabilities in AI systems.
## V. How To Use
Our model can be utilized in the same manner as Qwen or Deepseek-R1-Distill models.
For instance, you can easily start a service using [vLLM](https://github.com/vllm-project/vllm):
```bash
vllm serve Intelligent-Internet/II-Medical-32B-Preview
```
You can also easily start a service using [SGLang](https://github.com/sgl-project/sglang):
```bash
python -m sglang.launch_server --model Intelligent-Internet/II-Medical-32B-Preview
```
## VI. Usage Guidelines
- Recommended Sampling Parameters: temperature = 0.6, top_p = 0.9
- When using, explicitly request step-by-step reasoning and format the final answer within \boxed{} (e.g., "Please reason step-by-step, and put your final answer within \boxed{}.").
## VII. Limitations and Considerations
- Dataset may contain inherent biases from source materials
- Medical knowledge requires regular updates
- Please note that **It’s not suitable for medical use.**
## VIII. Citation
```bib
@misc{2025II-Medical-32B-Preview,
title={II-Medical-32B-Preview: Medical Reasoning Model},
author={Intelligent Internet},
year={2025}
}
```