reasoning benchmark
MBPP+ is an enhanced version of MBPP (Mostly Basic Python Problems) with 35x more test cases for evaluating solutions to Python programming problems.
Updated Sep 5, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelXI | Score74.10% | Percentile100.00% | Participants4 | EvidenceC | Evaluated |
| Rank02 | ModelAC | Score67.20% | Percentile66.67% | Participants4 | EvidenceC | Evaluated |
| Rank03 | ModelAC | Score63.20% | Percentile33.33% | Participants4 | EvidenceC | Evaluated |
| Rank04 | ModelBA | Score40.20% | Percentile0.00% | Participants4 | EvidenceC | Evaluated |
The leading models and scores on this benchmark.
A closer view of the leading scores on this benchmark.
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
What MBPP+ measures and how its scores work.
MBPP+ is a benchmark based on MBPP, which contains 974 crowd-sourced Python programming problems designed to be solvable by entry-level programmers and covering programming fundamentals and standard library functionality.
It measures performance on Python programming problems using the Score metric, reported as a ratio.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about MBPP+.
MiMo-V2.5-Pro is currently ranked first with 74.10%.
The current leaders are MiMo-V2.5-Pro (74.10%), Qwen2.5 32B Instruct (67.20%), and Qwen2.5 14B Instruct (63.20%).
Qwen2.5 14B Instruct has the lowest matched official input price at $0.35 input / $1.4 output per 1M tokens.
The fastest matched records are MiMo-V2.5-Pro (5.27 tok/s via DeepInfra).
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
It measures performance on Python programming problems using the Score metric, reported as a ratio.
Yes. Higher values rank better for this benchmark.
4 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.
Ranking basisThis mbpp+ AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
Selection summary
MiMo-V2.5-Pro currently leads MBPP+ with 74.10%. 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.