reasoning benchmark
CRUXEval-Input-CoT Leaderboard
CRUXEval input prediction task with Chain of Thought (CoT) prompting. Part of the CRUXEval benchmark for code reasoning, understanding, and execution evaluation. Given a Python function and its expected output, the task is to predict the appropriate input using chain-of-thought reasoning. Consists of 800 Python functions (3-13 lines) designed to evaluate code comprehension and reasoning capabilities.
Updated Aug 17, 2026
Models1
Model coverage1
MetricScore
EvidenceB
CRUXEval-Input-CoT Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAC | Score56.5% | Percentile100.0% | Participants1 | EvidenceC | Evaluated |
CRUXEval-Input-CoT Highlights
The leading models and scores on this benchmark.
The Top AI Models for CRUXEval-Input-CoT
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis cruxeval-input-cot 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.
- 01ACQwen2.5-Coder 7B InstructAlibaba Cloud / Qwen Team
- Score
- 56.5%
- Price
- $0.14 input / $0.29 output per 1M tokens
Strengths
- Ranks #1 of 1 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures CRUXEval-Input-CoT, not total model capability
Selection summary
Best AI Models for CRUXEval-Input-CoT
Qwen2.5-Coder 7B Instruct currently leads CRUXEval-Input-CoT with 56.5%. 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.
What is CRUXEval-Input-CoT?
What CRUXEval-Input-CoT measures and how its scores work.
CRUXEval input prediction task with Chain of Thought (CoT) prompting. Part of the CRUXEval benchmark for code reasoning, understanding, and execution evaluation. Given a Python function and its expected output, the task is to predict the appropriate input using chain-of-thought reasoning. Consists of 800 Python functions (3-13 lines) designed to evaluate code comprehension and reasoning capabilities.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- CRUXEval-Input-CoT
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- cruxeval-input-cot|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about CRUXEval-Input-CoT.
Which model scores highest on CRUXEval-Input-CoT?
Qwen2.5-Coder 7B Instruct is currently ranked first with 56.5%.
What does CRUXEval-Input-CoT measure?
CRUXEval input prediction task with Chain of Thought (CoT) prompting. Part of the CRUXEval benchmark for code reasoning, understanding, and execution evaluation. Given a Python function and its expected output, the task is to predict the appropriate input using chain-of-thought reasoning. Consists of 800 Python functions (3-13 lines) designed to evaluate code comprehension and reasoning capabilities.
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.