PneumaAI/DeepPulse-80B-Thinking-V0.1

DeepPulse-80B TCM Large Model Series

DeepPulse (深度把脉) is the core achievement of 心语心言's open-source Traditional Chinese Medicine (TCM) large model series. This series of models uses Qwen3-Next-80B as the base model and has undergone deep fine-tuning using a self-built high-quality TCM clinical medical dataset. This release includes two versions:

• DeepPulse-80B-Thinking-V0.1: Focuses on complex clinical reasoning and assisted diagnosis, achieving first place in total score in public evaluations, demonstrating top-tier logical reasoning capabilities in the TCM domain.
• DeepPulse-80B-Instruct-V0.1: Possesses excellent TCM instruction-following capabilities, suitable for a wide range of TCM Q&A and interactive scenarios, with a comprehensive ranking of sixth.

Public TCM Benchmark Metrics Comparison (MedBench - TCM-5CEval)

TCM-5CEval is an authoritative evaluation benchmark for TCM large models, comprising the following five subtasks that comprehensively assess the model's TCM capabilities:

• TCM-Exam (中医考试): Evaluates the mastery and application of fundamental TCM theories (Yin-Yang, Zang-Fu organs, etc.) and diagnostics knowledge.
• TCM-LitQA (典籍问答): Tests deep understanding and reasoning of classic TCM texts such as "Huangdi Neijing" and "Shanghan Lun".
• TCM-MRCD (临床诊疗): Simulates real clinical scenarios, evaluating the model's ability to analyze medical cases, perform pattern differentiation, and make prescription decisions.
• TCM-CMM (中药方剂): Measures the model's knowledge of Chinese materia medica properties, effects, compatibility contraindications, and formula applications.
• TCM-ClinNPT (非药物疗法): Assesses ability in acupoint selection for acupuncture, Tuina massage techniques, and pattern-based treatment for specific clinical scenarios.

No.	Model Name	Organization/Team Name	Release Date	Type	Parameters	Total Score	TCM-Exam	TCM-LitQA	TCM-MRCD	TCM-CMM	TCM-ClinNPT
1	DeepPulse-80B-Thinking-V0.1	心语心言	2025/12/23	开源	80B	71.3	83.0	45.5	75.4	84.9	67.6
2	HKR_TCM_HW_v1	港仔机器人主动健管团队	2025/12/12	闭源	671B	70.8	85.4	44.2	73.1	83.8	67.5
3	Gemini-2.5-Pro-nothinking	Google	2025/03/25	闭源	N/A	69.2	77.9	62.0	72.4	72.6	61.2
4	DeepSeek-V3.2	DeepSeek	2025/12/01	开源	671B	66.8	74.5	44.4	66.8	80.0	68.3
5	Grok-4	xAI	2025/07/09	闭源	N/A	66.6	73.0	59.3	68.4	68.0	64.2
6	DeepPulse-80B-Instruct-V0.1	心语心言	2025/12/23	开源	80B	66.2	74.4	40.7	70.6	79.7	65.6
7	Qwen3-235B-A22B-Thinking-2507	Alibaba	2025/08/17	开源	235B	64.8	75.5	40.3	68.5	78.2	61.5
8	Claude-Sonnet-4.5	Anthropic	2025/09/29	闭源	N/A	64.8	69.8	59.3	67.2	71.7	56.0
9	GPT-5	OpenAI	2025/08/07	闭源	N/A	63.6	75.0	51.9	64.1	66.6	60.6
10	Qwen3-Next-80B-A3B-Thinking	Alibaba	2025/09/15	开源	80B	63.5	76.0	38.2	66.2	77.9	59.4
11	Llama-4-maverick	Meta	2025/04/06	开源	400B	57.2	72.1	51.3	63.8	54.4	44.3
12	GPT-4o	OpenAI	2025/05/13	闭源	200B	55.9	66.5	46.9	60.9	57.1	47.9

Note: "N/A" in the Parameters column indicates that the model's parameter count has not been publicly disclosed.

Except for DeepSeek-V3.2, Qwen3-235B-A22B-Thinking-2507, Qwen3-Next-80B-A3B-Thinking which are self-tested deployment data, other models reference publicly available leaderboard data.

TCM-5CEval: https://medbench.opencompass.org.cn/track-detail/tcmeval