Baichuan-M2-32B is Baichuan AI's medical-enhanced reasoning model, the second medical model released by Baichuan. Designed for real-world medical reasoning tasks, this model builds upon Qwen2.5-32B with an innovative Large Verifier System. Through domain-specific fine-tuning on real-world medical questions, it achieves breakthrough medical performance while maintaining strong general capabilities.
Model Features:
Baichuan-M2 incorporates three core technical innovations: First, through the Large Verifier System, it combines medical scenario characteristics to design a comprehensive medical verification framework, including patient simulators and multi-dimensional verification mechanisms; second, through medical domain adaptation enhancement via Mid-Training, it achieves lightweight and efficient medical domain adaptation while preserving general capabilities; finally, it employs a multi-stage reinforcement learning strategy, decomposing complex RL tasks into hierarchical training stages to progressively enhance the model's medical knowledge, reasoning, and patient interaction capabilities.
Core Highlights:
🏆 World's Leading Open-Source Medical Model: Outperforms all open-source models and many proprietary models on HealthBench, achieving medical capabilities closest to GPT-5
🧠 Doctor-Thinking Alignment: Trained on real clinical cases and patient simulators, with clinical diagnostic thinking and robust patient interaction capabilities
⚡ Efficient Deployment: Supports 4-bit quantization for single-RTX4090 deployment, with 58.5% higher token throughput in MTP version for single-user scenarios
📊 Performance Metrics
HealthBench Scores
Model Name
HealthBench
HealthBench-Hard
HealthBench-Consensus
Baichuan-M2
60.1
34.7
91.5
gpt-oss-120b
57.6
30
90
Qwen3-235B-A22B-Thinking-2507
55.2
25.9
90.6
Deepseek-R1-0528
53.6
22.6
91.5
GLM-4.5
47.8
18.7
85.3
Kimi-K2
43
10.7
90.9
gpt-oss-20b
42.5
10.8
82.6
General Performance
Benchmark
Baichuan-M2-32B
Qwen3-32B (Thinking)
AIME24
83.4
81.4
AIME25
72.9
72.9
Arena-Hard-v2.0
45.8
44.5
CFBench
77.6
75.7
WritingBench
8.56
7.90
Note: AIME uses max_tokens=64k, others use 32k; temperature=0.6 for all tests.
