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agents benchmark

VIBE-Pro Leaderboard

VIBE-Pro evaluates LLMs on professional-grade full-stack application development tasks across web, mobile, and backend applications.

Updated Sep 5, 2026

Models2
Model coverage2
MetricScore
EvidenceB

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VIBE-Pro Ranking

Higher score ranks better on this benchmark.

2 rows
Columns

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Sort by
Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelMIMiniMax M2.7MiniMaxScore55.60%Percentile100.00%Participants2EvidenceCEvaluatedSep 8, 2026
Rank02ModelMIMiniMax M2.5MiniMaxScore54.20%Percentile0.00%Participants2EvidenceCEvaluatedSep 8, 2026

VIBE-Pro Highlights

The leading models and scores on this benchmark.

Rank #1MiniMax M2.755.60%Rank #2MiniMax M2.554.20%

VIBE-Pro Score Distribution

A closer view of the leading scores on this benchmark.

VIBE-Pro

The Top AI Models for VIBE-Pro

The first five results on this benchmark, with official price and output speed added where the model identity can be matched.

What is VIBE-Pro?

What VIBE-Pro measures and how its scores work.

VIBE-Pro is an advanced version of the VIBE (Visual & Interactive Benchmark for Execution) benchmark for evaluating LLMs on full-stack application development tasks.

It measures model performance across complex real-world development scenarios involving web, mobile, and backend applications, with higher difficulty than the standard VIBE benchmark.

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

Family
VIBE-Pro
Modality
text
Primary category
agents
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 VIBE-Pro.

Which model scores highest on VIBE-Pro?

MiniMax M2.7 is currently ranked first with 55.60%.

What are the top three models on VIBE-Pro?

The current leaders are MiniMax M2.7 (55.60%) and MiniMax M2.5 (54.20%).

Which VIBE-Pro model has the lowest official input price?

MiniMax M2.7 has the lowest matched official input price at $0.30 input / $1.2 output per 1M tokens.

Which models are fastest among VIBE-Pro results?

The fastest matched records are MiniMax M2.5 (100.00 tok/s via MiniMax).

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 VIBE-Pro measure?

It measures model performance across complex real-world development scenarios involving web, mobile, and backend applications, with higher difficulty than the standard VIBE benchmark.

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 vibe-pro 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
    MI
    MiniMax M2.7MiniMax
    Score
    55.60%
    Price
    $0.30 input / $1.2 output per 1M tokens

    Strengths

    • Ranks #1 of 2 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures VIBE-Pro, not total model capability
  2. 02
    MI
    MiniMax M2.5MiniMax
    Score
    54.20%
    Price
    $0.30 input / $1.2 output per 1M tokens
    Speed
    Up to 100.00 tok/s via MiniMax

    Strengths

    • Ranks #2 of 2 compared models
    • 0th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures VIBE-Pro, not total model capability

Selection summary

Best AI Models for VIBE-Pro

MiniMax M2.7 currently leads VIBE-Pro with 55.60%. 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 #1MiniMax M2.755.60% · $0.30 input / $1.2 output per 1M tokens
Benchmark rank #2MiniMax M2.554.20% · $0.30 input / $1.2 output per 1M tokens