llmboard.aiAI model intelligence
Home

Model Rankings

OverallOpen ModelsAgentCodingReasoningMathKnowledgeInstruction FollowingTextVision
Image GenerationImage Editing
Video GenerationImage to VideoVideo Editing
Text to SpeechSpeech to Text
Embeddings

Efficiency

Chat Token PricingImage PricingVideo PricingAudio Pricing
Chat Speed & LatencyProvider Reliability

Benchmarks

GPQAMMLU-ProAIME 2025SWE-Bench VerifiedMMLUHumanity's Last ExamLiveCodeBenchMATHHumanEvalMMMU-Pro
All Benchmarks

Tools

Model DirectoryCompare Models

Scoring & Data

Scoring & Data
393 models668 benchmarks

Leaderboard Center

Overall RankingCodingCore BenchmarksPrice & ValueRuntime Performance

Modalities

All ModelsImage GenerationImage EditingVideo GenerationImage-to-VideoVideo EditingText-to-SpeechSpeech-to-TextEmbeddings

Data & Methods

Scoring MethodAll BenchmarksReasoningMath

Vendors

All VendorsOpenAIAnthropicGoogle
llmboard.aiCopyright 2026 llmboard.ai

reasoning benchmark

CruxEval-O Leaderboard

CruxEval-O is the output prediction task of the CRUXEval benchmark, designed to evaluate code reasoning, understanding, and execution capabilities. It consists of 800 Python functions (3-13 lines) where models must predict the output given a function and input. The benchmark tests fundamental code execution reasoning abilities and goes beyond simple code generation to assess deeper understanding of program behavior.

Updated Aug 17, 2026

Models1
Model coverage1
MetricScore
EvidenceB

On this page

  • Ranking
  • Highlights
  • Top models
  • About
  • FAQ

CruxEval-O Ranking

Higher score ranks better on this benchmark.

1 rows
Columns

Show columns

Sort by
Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelMACodestral-22BMistral AIScore51.3%Percentile100.0%Participants1EvidenceCEvaluatedAug 17, 2026

CruxEval-O Highlights

The leading models and scores on this benchmark.

Rank #1Codestral-22B51.3%

The Top AI Models for CruxEval-O

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

Ranking basisThis cruxeval-o 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.

  1. 01
    MA
    Codestral-22BMistral AI
    Score
    51.3%

    Strengths

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

    Considerations

    • This result measures CruxEval-O, not total model capability

Selection summary

Best AI Models for CruxEval-O

Codestral-22B currently leads CruxEval-O with 51.3%. 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 #1Codestral-22B51.3%

What is CruxEval-O?

What CruxEval-O measures and how its scores work.

CruxEval-O is the output prediction task of the CRUXEval benchmark, designed to evaluate code reasoning, understanding, and execution capabilities. It consists of 800 Python functions (3-13 lines) where models must predict the output given a function and input. The benchmark tests fundamental code execution reasoning abilities and goes beyond simple code generation to assess deeper understanding of program behavior.

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

Family
CruxEval-O
Modality
text
Primary category
reasoning
Score direction
higher
LLMBoard eligible
No
Evaluation key
cruxeval-o|llm-stats-current

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

FAQ

Common questions about CruxEval-O.

Which model scores highest on CruxEval-O?

Codestral-22B is currently ranked first with 51.3%.

What does CruxEval-O measure?

CruxEval-O is the output prediction task of the CRUXEval benchmark, designed to evaluate code reasoning, understanding, and execution capabilities. It consists of 800 Python functions (3-13 lines) where models must predict the output given a function and input. The benchmark tests fundamental code execution reasoning abilities and goes beyond simple code generation to assess deeper understanding of program behavior.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

1 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.