reasoning benchmark
MBPP EvalPlus Leaderboard
MBPP (Mostly Basic Python Problems) is a benchmark of 974 crowd-sourced Python programming problems designed to be solvable by entry-level programmers. EvalPlus extends MBPP with significantly more test cases (35x) for more rigorous evaluation of LLM-synthesized code, providing high-quality and precise evaluation.
Updated Aug 17, 2026
Models2
Model coverage2
MetricScore
EvidenceB
MBPP EvalPlus Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelME | Score88.6% | Percentile100.0% | Participants2 | EvidenceC | Evaluated |
| Rank02 | ModelME | Score87.6% | Percentile0.0% | Participants2 | EvidenceC | Evaluated |
MBPP EvalPlus Highlights
The leading models and scores on this benchmark.
MBPP EvalPlus Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for MBPP EvalPlus
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis mbpp evalplus AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
- 01ME
- Score
- 88.6%
- Speed
- Up to 100 tok/s via Bedrock
Strengths
- Ranks #1 of 2 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures MBPP EvalPlus, not total model capability
- 02ME
- Score
- 87.6%
- Speed
- Up to 2,220 tok/s via Cerebras
Strengths
- Ranks #2 of 2 compared models
- 0th percentile on this benchmark
- C evidence result
Considerations
- This result measures MBPP EvalPlus, not total model capability
Selection summary
Best AI Models for MBPP EvalPlus
Llama 3.1 405B Instruct currently leads MBPP EvalPlus with 88.6%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.
What is MBPP EvalPlus?
What MBPP EvalPlus measures and how its scores work.
MBPP (Mostly Basic Python Problems) is a benchmark of 974 crowd-sourced Python programming problems designed to be solvable by entry-level programmers. EvalPlus extends MBPP with significantly more test cases (35x) for more rigorous evaluation of LLM-synthesized code, providing high-quality and precise evaluation.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- MBPP EvalPlus
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- mbpp-evalplus|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about MBPP EvalPlus.
Which model scores highest on MBPP EvalPlus?
Llama 3.1 405B Instruct is currently ranked first with 88.6%.
What does MBPP EvalPlus measure?
MBPP (Mostly Basic Python Problems) is a benchmark of 974 crowd-sourced Python programming problems designed to be solvable by entry-level programmers. EvalPlus extends MBPP with significantly more test cases (35x) for more rigorous evaluation of LLM-synthesized code, providing high-quality and precise evaluation.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
2 model results are currently shown.
Does this benchmark affect the overall score?
No. This benchmark is shown for reference but does not contribute to the overall score.