# ShizhenGPT

TCM language models have been trained on under 1GB of text and handle text alone, while TCM diagnosis itself draws on looking, listening, smelling and pulse-taking. ShizhenGPT pairs more than 100GB of text from 3,256 TCM books and web sources with over 200GB of multimodal data, including 1.2M annotated images, 200+ hours of audio and pulse, smell and ECG signals, through two-stage pretraining and instruction tuning. On five 2024–2025 TCM exams ShizhenGPT-32B averages 78.1 against 84.0 for DeepSeek-R1-671B, and on a 7,204-question TCM vision benchmark it scores 63.6 against 61.4 for Gemini-3-Pro.

TCM language models have been trained on under 1GB of text and handle text alone, while TCM diagnosis itself draws on looking, listening, smelling and pulse-taking. ShizhenGPT pairs more than 100GB of text from 3,256 TCM books and web sources with over 200GB of multimodal data, including 1.2M annotated images, 200+ hours of audio and pulse, smell and ECG signals, through two-stage pretraining and instruction tuning. On five 2024–2025 TCM exams ShizhenGPT-32B averages 78.1 against 84.0 for DeepSeek-R1-671B, and on a 7,204-question TCM vision benchmark it scores 63.6 against 61.4 for Gemini-3-Pro.