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reasoning benchmark

MBPP

MBPP (Mostly Basic Python Problems) is a benchmark of 974 crowd-sourced Python programming problems designed to be solvable by entry-level programmers. Each problem consists of a task description, code solution, and 3 automated test cases covering programming fundamentals and standard library functionality.

Updated Aug 11, 2026

Models33
Model coverage33
MetricPass@1
EvidenceB

On this page

  • Ranking
  • Distribution
  • Highlights
  • About
  • FAQ

MBPP Ranking

Higher pass@1 ranks better on this benchmark.

33 rows
Columns

Show columns

01SASarvam-30BSarvam AI92.7%100.0%33CAug 11, 2026
02NVLlama-3.3 Nemotron Super 49B v1NVIDIA91.3%96.9%33CAug 11, 2026
03ACQwen2.5-Coder 32B InstructAlibaba Cloud / Qwen Team90.2%93.8%33CAug 11, 2026
04OPMiniCPM-SALAOpenBMB89.1%90.6%33CAug 11, 2026
05ACQwen2.5 72B InstructAlibaba Cloud / Qwen Team88.2%87.5%33CAug 11, 2026
06NVLlama 3.1 Nemotron Nano 8B V1NVIDIA84.6%84.4%33CAug 11, 2026
07ACQwen2.5 32B InstructAlibaba Cloud / Qwen Team84.0%81.3%33CAug 11, 2026
08ACQwen2.5 VL 32B InstructAlibaba Cloud / Qwen Team84.0%78.1%33CAug 11, 2026
09ACQwen2.5-Coder 7B InstructAlibaba Cloud / Qwen Team83.5%75.0%33CAug 11, 2026
10ACQwen2.5 14B InstructAlibaba Cloud / Qwen Team82.0%71.9%33CAug 11, 2026
11ACQwen3 235B A22BAlibaba Cloud / Qwen Team81.4%68.8%33CAug 11, 2026
12MIPhi-3.5-MoE-instructMicrosoft80.8%65.6%33CAug 11, 2026
13ACQwen2 72B InstructAlibaba Cloud / Qwen Team80.2%62.5%33CAug 11, 2026
14ACQwen2.5 7B InstructAlibaba Cloud / Qwen Team79.2%59.4%33CAug 11, 2026
15MACodestral-22BMistral AI78.2%56.3%33CAug 11, 2026
16MELlama 4 MaverickMeta77.6%53.1%33CAug 11, 2026
17GOGemini DiffusionGoogle76.0%50.0%33CAug 11, 2026
18MAMistral Small 3.1 24B InstructMistral AI74.7%46.9%33CAug 11, 2026
19GOGemma 3 27BGoogle74.4%43.8%33CAug 11, 2026
20ACQwen2.5-Omni-7BAlibaba Cloud / Qwen Team73.2%40.6%33CAug 11, 2026
21GOGemma 3 12BGoogle73.0%37.5%33CAug 11, 2026
22MAMistral Small 3 24B BaseMistral AI69.6%34.4%33CAug 11, 2026
23MIPhi-3.5-mini-instructMicrosoft69.6%31.3%33CAug 11, 2026
24MELlama 4 ScoutMeta67.8%28.1%33CAug 11, 2026
25ACQwen2 7B InstructAlibaba Cloud / Qwen Team67.2%25.0%33CAug 11, 2026
26GOGemma 3n E4B InstructedGoogle63.6%21.9%33CAug 11, 2026
27GOGemma 3n E4B Instructed LiteRT PreviewGoogle63.6%18.8%33CAug 11, 2026
28GOGemma 3 4BGoogle63.2%15.6%33CAug 11, 2026
29GOGemma 2 27BGoogle62.6%12.5%33CAug 11, 2026
30GOGemma 3n E2B InstructedGoogle56.6%9.4%33CAug 11, 2026
31GOGemma 3n E2B Instructed LiteRT (Preview)Google56.6%6.3%33CAug 11, 2026
32GOGemma 2 9BGoogle52.4%3.1%33CAug 11, 2026
33GOGemma 3 1BGoogle35.2%0.0%33CAug 11, 2026

MBPP Score Distribution

A closer view of the leading scores on this benchmark.

MBPP

MBPP Highlights

The leading models and scores on this benchmark.

Rank #1Sarvam-30B92.7%Rank #2Llama-3.3 Nemotron Super 49B v191.3%Rank #3Qwen2.5-Coder 32B Instruct90.2%Rank #4MiniCPM-SALA89.1%

What is MBPP?

What MBPP 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. Each problem consists of a task description, code solution, and 3 automated test cases covering programming fundamentals and standard library functionality.

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
MBPP
Modality
text
Primary category
reasoning
Score direction
higher
LLMBoard eligible
Yes
Evaluation key
mbpp|llm-stats-current

Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about MBPP.

Which model scores highest on MBPP?

Sarvam-30B is currently ranked first with 92.7%.

What does MBPP measure?

MBPP (Mostly Basic Python Problems) is a benchmark of 974 crowd-sourced Python programming problems designed to be solvable by entry-level programmers. Each problem consists of a task description, code solution, and 3 automated test cases covering programming fundamentals and standard library functionality.

Is a higher pass@1 better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

33 model results are currently shown.

Does this benchmark affect the overall score?

Yes. This benchmark can contribute to the current LLMBoard capability score.