MedMCQA

Key facts

Domain

Clinical medicine Modern medicine

Content

Question banks and benchmarks · QA, dialogue and instruction dataLarge-scale multiple-choice QA dataset of AIIMS & NEET PG medical entrance exam questions covering 2.4k healthcare topics and 21 medical subjects, with expert explanations for answers.

Size

—As stated: more than 194k high-quality AIIMS & NEET PG entrance exam MCQs

Language / modality

English / Text

Publisher

openlifescienceai

Year

—

Expert review

—

Verification

Verified: license text seen

Commercial use of MedMCQA

Commercial use: Yes. License status: Permissive.

Conditions

Notice kept

Quoted statements and their sources are in MedMCQA license evidence.

Verdicts record what sources state and are not legal advice.

Tags

Task format

Multiple-choice (single answer)

Quoted from the sourceMedMCQA is a large-scale, Multiple-Choice Question Answering (MCQA) dataset designed to address real-world medical entrance exam questions.Snapshot s95

Intended use

Fine-tuning

Quoted from the sourceThe dataset can be used to train a model for multi-choice questions answering, open domain questions answering.Snapshot s95

Evaluation

Quoted from the sourceThe development set consists of NEET PG exam MCQs (years 2001-present) to approximate real exam evaluation.Snapshot s95

Specialty

Multi-specialty

Quoted from the sourcecovering 2.4k healthcare topics and 21 medical subjectsSnapshot s95

Source type

Official publication

Quoted from the sourceHistorical Exam questions from official websites - AIIMS & NEET PG (1991- present)Snapshot s95

Annotation depth

With explanations

Quoted from the source- `exp` : Expert's explanation of the answerSnapshot s95

Official split

Train and test splits

Quoted from the sourceTo enable that, a predefined split of the dataset is provided.Snapshot s95

Benchmark status

Public leaderboard

Quoted from the source- **Leaderboard:** https://paperswithcode.com/dataset/medmcqaSnapshot s95

Author-statedInferredHuman-confirmed

MedMCQA license evidence 3

1. Hugging Face card metadataPage opened
   Apache-2.0

   Third-party text · Hugging Face card metadata"apache-2.0"

   Statement found in snapshot s97 (api-hf)

   huggingface.co2026-11-12 · s97
2. Hugging Face card metadataPage opened
   Apache-2.0

   Third-party text · Hugging Face card metadatalicense: - apache-2.0

   Statement found in snapshot s95 (readme)

   huggingface.co2026-11-12 · s95
3. Dataset pagePage opened
   Apache-2.0

   Third-party text · Dataset pageLicense: apache-2.0

   Statement found in snapshot s96 (page)

   huggingface.co2026-11-12 · s96

Source and lineage

No upstream or downstream datasets recorded.

Known issues with MedMCQA

• The card's limitations, biases, and personal/sensitive-information sections are all placeholders marked "[Needs More Information]".

Downloading MedMCQA and API access

No file on Mdexa (see the verdict). Get it from the source and confirm the terms there:

• huggingface.co/datasets/openlifescienceai/medmcqa

curl -L --create-dirs -o ".gitattributes" "https://huggingface.co/datasets/openlifescienceai/medmcqa/resolve/91c6572c454088bf71b679ad90aa8dffcd0d5868/.gitattributes"
curl -L --create-dirs -o "README.md" "https://huggingface.co/datasets/openlifescienceai/medmcqa/resolve/91c6572c454088bf71b679ad90aa8dffcd0d5868/README.md"
curl -L --create-dirs -o "data/test-00000-of-00001.parquet" "https://huggingface.co/datasets/openlifescienceai/medmcqa/resolve/91c6572c454088bf71b679ad90aa8dffcd0d5868/data/test-00000-of-00001.parquet"
echo "1d308841f0c82df363d3d638b33b69b8abd266b1e615ae5d2607dbb24c70beb1  data/test-00000-of-00001.parquet" | sha256sum -c
curl -L --create-dirs -o "data/train-00000-of-00001.parquet" "https://huggingface.co/datasets/openlifescienceai/medmcqa/resolve/91c6572c454088bf71b679ad90aa8dffcd0d5868/data/train-00000-of-00001.parquet"
echo "b119434ba551517a6ec0ba1f7e0b4c029165ed284a4704f262ce37c791c493c5  data/train-00000-of-00001.parquet" | sha256sum -c
curl -L --create-dirs -o "data/validation-00000-of-00001.parquet" "https://huggingface.co/datasets/openlifescienceai/medmcqa/resolve/91c6572c454088bf71b679ad90aa8dffcd0d5868/data/validation-00000-of-00001.parquet"
echo "b768a1ea34afc9f80d3106d9b21f80fa8a00ec450a1f6cd641af72ca9e591021  data/validation-00000-of-00001.parquet" | sha256sum -c

Citing MedMCQA

Mdexa, MedMCQA, https://mdexa.com/datasets/medmcqa/, verified 2026-11-14.

Machine-readable

medmcqa.jsonmedmcqa.mdcatalog.json

Listed in

• Multiple-choice evaluation sets with explanations
• Datasets with official train and test splits
• Benchmarks with a leaderboard or a human baseline
• Medical datasets for evaluation that have a permissive license
• Medical datasets for fine-tuning that have a permissive license
• Medical datasets built from web-scraped content that have a permissive license
• Multiple-choice (single answer) medical datasets that have a permissive license
• Medical datasets built from exam questions that have a permissive license

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