medbench.kr

GLM-5.3 753B-A40B on clinicalqa@0

Run a4cc8ae1a524 · baseline tier · evaluated 2026-10-29

Scores

accuracy0.909 (0.892–0.926)
parse rate0.998
n1045
tokens (in / out)478883 / 260058
cost (USD)0.0000

By category

Allergy and Immunology0.972 (n=36)
Cardiology0.921 (n=89)
Dermatology0.917 (n=12)
Emergency Medicine1.000 (n=32)
Endocrinology0.926 (n=68)
Endocrinology, metabolic, and nutritional disorders1.000 (n=1)
Forensic Medicine1.000 (n=1)
Gastroenterology0.946 (n=112)
General Surgery0.914 (n=58)
Geriatric Medicine1.000 (n=1)
Gynecology0.800 (n=70)
Hematology and Oncology0.979 (n=48)
Infectious Diseases0.885 (n=52)
Musculoskeletal (e.g., costochondritis)1.000 (n=1)
Nephrology0.838 (n=111)
Neurology / Neurosurgery0.939 (n=49)
Obstetrics0.833 (n=18)
Ophthalmology1.000 (n=1)
Orthopedic Surgery1.000 (n=24)
Otolaryngology1.000 (n=14)
Otolaryngology (ENT)0.929 (n=14)
Pediatrics0.911 (n=56)
Pharmacology1.000 (n=1)
Psychiatry0.867 (n=45)
Pulmonology (Respiratory Medicine)0.908 (n=65)
Radiology1.000 (n=1)
Rheumatology0.898 (n=49)
Urology0.846 (n=13)
Vascular Surgery1.000 (n=2)
nan1.000 (n=1)

Reuse this result

Download per-item predictions (parquet) · JSON

@misc{medbench_a4cc8ae1a524,
  title = {GLM-5.3 753B-A40B on Korean clinical knowledge (KMLE-level MCQ) (clinicalqa@0)},
  author = {{medbench.kr}},
  year = {2026},
  howpublished = {\url{https://medbench.kr/r/a4cc8ae1a524}},
  note = {Evaluated 2026-10-29, harness p0.1, run key 14b562a15246}
}

Versions

model digestkgpu/glm-5.3-ax-753b-a40b
task spec hash77e37cd0ca6bded7fba03792ec1922342b3f6a7dc3ce602881ce196e6aa7377c
harnessp0.1
run key14b562a152460ac7214c4eabcfc174363d08845169bd465f386a4be0802ca56a
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