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reasoning benchmark

MBPP EvalPlus Leaderboard

MBPP EvalPlus is a benchmark of 974 crowd-sourced Python programming problems, extended with 35x more test cases than MBPP.

Updated Sep 5, 2026

Models2
Model coverage2
MetricScore
EvidenceB

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MBPP EvalPlus Ranking

Higher score ranks better on this benchmark.

2 rows
Columns

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Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelMELlama 3.1 405B InstructMetaScore88.60%Percentile100.00%Participants2EvidenceCEvaluatedSep 8, 2026
Rank02ModelMELlama 3.3 70B InstructMetaScore87.60%Percentile0.00%Participants2EvidenceCEvaluatedSep 8, 2026

MBPP EvalPlus Highlights

The leading models and scores on this benchmark.

Rank #1Llama 3.1 405B Instruct88.60%Rank #2Llama 3.3 70B Instruct87.60%

MBPP EvalPlus Score Distribution

A closer view of the leading scores on this benchmark.

MBPP EvalPlus

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.

What is MBPP EvalPlus?

What MBPP EvalPlus measures and how its scores work.

MBPP EvalPlus is an EvalPlus extension of MBPP, which consists of Python programming problems designed to be solvable by entry-level programmers.

It measures the performance of LLM-synthesized code using additional test cases, reported as Score in ratio units.

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
overall

LLM Stats. 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 88.60%.

What are the top three models on MBPP EvalPlus?

The current leaders are Llama 3.1 405B Instruct (88.60%) and Llama 3.3 70B Instruct (87.60%).

Which MBPP EvalPlus model has the lowest official input price?

No matched official input price is currently available.

Which models are fastest among MBPP EvalPlus results?

The fastest matched records are Llama 3.3 70B Instruct (2,220.00 tok/s via Cerebras) and Llama 3.1 405B Instruct (42.00 tok/s via Google).

Does the highest score result prove overall model quality?

No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.

What does MBPP EvalPlus measure?

It measures the performance of LLM-synthesized code using additional test cases, reported as Score in ratio units.

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.

Ranking basisThis mbpp evalplus AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.

  1. 01
    ME
    Llama 3.1 405B InstructMeta
    Score
    88.60%
    Speed
    Up to 42.00 tok/s via Google

    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
  2. 02
    ME
    Llama 3.3 70B InstructMeta
    Score
    87.60%
    Speed
    Up to 2,220.00 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 88.60%. 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.

Benchmark rank #1Llama 3.1 405B Instruct88.60% · Up to 42.00 tok/s via Google
Benchmark rank #2Llama 3.3 70B Instruct87.60% · Up to 2,220.00 tok/s via Cerebras