Mostly Basic Python Problems (MBPP).

Mostly Basic Python Problems (MBPP) is a benchmark for function-level Python code generation consisting of short, entry-level programming problems paired with natural language task descriptions, reference solutions, and automated unit tests. The public Hugging Face versions contain 974 problems (with a sanitized subset of 427 examples available) covering basic numeric, list, and string manipulations and common standard-library usage. MBPP was introduced to evaluate the ability of neural models to synthesize short Python programs from natural language prompts (used in few-shot and fine-tuning evaluations); the dataset is commonly used to report pass@k or exact-match test metrics for code generation models. License: CC BY 4.0.

Best published scores.

1 result indexed across 1 metric. Shaded row marks current SOTA; ties broken by submission date.

Primary

Pass@1 · higher is better

1 steps
of state of the art.

Each row below marks a model that broke the previous record on Pass@1. Intermediate submissions are kept in the leaderboard above; only SOTA-setting entries are re-listed here.

Higher scores win. Each subsequent entry improved upon the previous best.

1. Dec 19, 2024Qwen2.5-72B-Instruct88.20

1 paper
tied to this benchmark.

Every paper below corresponds to at least one row in the leaderboard above. Click through for the arXiv preprint and, when available, the reference implementation.

Neighbouring benchmarks.

Other Coding Agents datasets on Codesota.

Have a score that beats
this table?

Submit a checkpoint and a reproduction script. We will run it, publish the score, and — if it takes the top — annotate the step on the progress chart with your name.

• 01A public checkpoint or API endpoint
• 02A reproduction script with frozen commit + seed
• 03Declared evaluation environment (Python, deps)
• 04One row per metric declared by this dataset
• 05A contact so we can follow up on discrepancies