reasoning benchmark
BigCodeBench-Hard is a subset of 148 challenging programming tasks from BigCodeBench, designed to evaluate large language models' ability to solve complex, real-world programming problems. These tasks require diverse function calls from multiple libraries across 7 domains including computation, networking, data analysis, and visualization. The benchmark tests compositional reasoning and the ability to implement complex instructions that span 139 libraries with an average of 2.8 libraries per task.
Updated Aug 17, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAC | Score27.0% | Percentile100.0% | Participants1 | EvidenceC | Evaluated |
The leading models and scores on this benchmark.
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis bigcodebench-hard 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.
Selection summary
Qwen2.5-Coder 32B Instruct currently leads BigCodeBench-Hard with 27.0%. 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 BigCodeBench-Hard measures and how its scores work.
BigCodeBench-Hard is a subset of 148 challenging programming tasks from BigCodeBench, designed to evaluate large language models' ability to solve complex, real-world programming problems. These tasks require diverse function calls from multiple libraries across 7 domains including computation, networking, data analysis, and visualization. The benchmark tests compositional reasoning and the ability to implement complex instructions that span 139 libraries with an average of 2.8 libraries per task.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about BigCodeBench-Hard.
Qwen2.5-Coder 32B Instruct is currently ranked first with 27.0%.
BigCodeBench-Hard is a subset of 148 challenging programming tasks from BigCodeBench, designed to evaluate large language models' ability to solve complex, real-world programming problems. These tasks require diverse function calls from multiple libraries across 7 domains including computation, networking, data analysis, and visualization. The benchmark tests compositional reasoning and the ability to implement complex instructions that span 139 libraries with an average of 2.8 libraries per task.
Yes. Higher values rank better for this benchmark.
1 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.