medbench.kr

gpt-oss 20B on clinicalqa@0

Run 75310a96c0a0 · baseline tier · evaluated 2026-10-29

Scores

accuracy0.852 (0.831–0.874)
parse rate0.995
n1045
tokens (in / out)460978 / 552925
cost (USD)0.0909

By category

Allergy and Immunology0.806 (n=36)
Cardiology0.899 (n=89)
Dermatology0.583 (n=12)
Emergency Medicine0.969 (n=32)
Endocrinology0.838 (n=68)
Endocrinology, metabolic, and nutritional disorders1.000 (n=1)
Forensic Medicine1.000 (n=1)
Gastroenterology0.893 (n=112)
General Surgery0.810 (n=58)
Geriatric Medicine1.000 (n=1)
Gynecology0.743 (n=70)
Hematology and Oncology0.979 (n=48)
Infectious Diseases0.788 (n=52)
Musculoskeletal (e.g., costochondritis)1.000 (n=1)
Nephrology0.865 (n=111)
Neurology / Neurosurgery0.939 (n=49)
Obstetrics0.833 (n=18)
Ophthalmology1.000 (n=1)
Orthopedic Surgery0.875 (n=24)
Otolaryngology1.000 (n=14)
Otolaryngology (ENT)0.786 (n=14)
Pediatrics0.821 (n=56)
Pharmacology1.000 (n=1)
Psychiatry0.800 (n=45)
Pulmonology (Respiratory Medicine)0.846 (n=65)
Radiology0.000 (n=1)
Rheumatology0.857 (n=49)
Urology0.692 (n=13)
Vascular Surgery1.000 (n=2)
nan0.000 (n=1)

Reuse this result

Download per-item predictions (parquet) · JSON

@misc{medbench_75310a96c0a0,
  title = {gpt-oss 20B on Korean clinical knowledge (KMLE-level MCQ) (clinicalqa@0)},
  author = {{medbench.kr}},
  year = {2026},
  howpublished = {\url{https://medbench.kr/r/75310a96c0a0}},
  note = {Evaluated 2026-10-29, harness p0.1, run key be9fbff2519a}
}

Versions

modelgpt-oss-20b-a3.6b (OpenAI)
task spec hash77e37cd0ca6bded7fba03792ec1922342b3f6a7dc3ce602881ce196e6aa7377c
harnessp0.1
run keybe9fbff2519a2670f151915d7243b62070818174e6d7c28827d237ee71a877c4
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