medbench.kr

MedGemma 1.5 4B on clinicalqa@0

Run 7993fc36d3a5 · baseline tier · evaluated 2026-10-29

Scores

accuracy0.765 (0.739–0.789)
parse rate0.995
n1045
tokens (in / out)399078 / 1124133
cost (USD)0.1244

By category

Allergy and Immunology0.722 (n=36)
Cardiology0.854 (n=89)
Dermatology0.583 (n=12)
Emergency Medicine0.781 (n=32)
Endocrinology0.824 (n=68)
Endocrinology, metabolic, and nutritional disorders1.000 (n=1)
Forensic Medicine1.000 (n=1)
Gastroenterology0.821 (n=112)
General Surgery0.690 (n=58)
Geriatric Medicine1.000 (n=1)
Gynecology0.586 (n=70)
Hematology and Oncology0.896 (n=48)
Infectious Diseases0.692 (n=52)
Musculoskeletal (e.g., costochondritis)1.000 (n=1)
Nephrology0.721 (n=111)
Neurology / Neurosurgery0.796 (n=49)
Obstetrics0.833 (n=18)
Ophthalmology1.000 (n=1)
Orthopedic Surgery0.667 (n=24)
Otolaryngology0.857 (n=14)
Otolaryngology (ENT)0.786 (n=14)
Pediatrics0.732 (n=56)
Pharmacology1.000 (n=1)
Psychiatry0.689 (n=45)
Pulmonology (Respiratory Medicine)0.831 (n=65)
Radiology1.000 (n=1)
Rheumatology0.776 (n=49)
Urology0.769 (n=13)
Vascular Surgery1.000 (n=2)
nan1.000 (n=1)

Reuse this result

Download per-item predictions (parquet) · JSON

@misc{medbench_7993fc36d3a5,
  title = {MedGemma 1.5 4B on Korean clinical knowledge (KMLE-level MCQ) (clinicalqa@0)},
  author = {{medbench.kr}},
  year = {2026},
  howpublished = {\url{https://medbench.kr/r/7993fc36d3a5}},
  note = {Evaluated 2026-10-29, harness p0.1, run key dca8c80bee5d}
}

Versions

model digestkgpu/medgemma-1.5-4b
task spec hash77e37cd0ca6bded7fba03792ec1922342b3f6a7dc3ce602881ce196e6aa7377c
harnessp0.1
run keydca8c80bee5d4f700d225c14e5d8cdd2c15dbc4ecc3d801025230c74f4a9b6b1
config{"max_tokens": 16384, "prompt": "clinicalqa-p0", "temperature": 0}

Data

ClinicalQA: Korean Medical Knowledge QA Benchmark, CC BY 4.0 (upstream Apache-2.0).

SNUH-HARI. ClinicalQA: Korean Medical Knowledge QA Benchmark. Seoul National University Hospital Healthcare AI Research Institute, 2025. doi:10.23421/2026.0800