reasoning benchmark
RepoBench
RepoBench is a benchmark for evaluating repository-level code auto-completion systems through three interconnected tasks: RepoBench-R (retrieval of relevant code snippets across files), RepoBench-C (code completion with cross-file and in-file context), and RepoBench-P (pipeline combining retrieval and prediction). Supports Python and Java programming languages and addresses the gap in evaluating real-world, multi-file programming scenarios by providing a more complete comparison of performance in auto-completion systems.
Updated Aug 11, 2026
Models1
Model coverage1
MetricScore
EvidenceB
RepoBench Ranking
Higher score ranks better on this benchmark.
| 01 | MA | 34.0% | 100.0% | 1 | C |
RepoBench Highlights
The leading models and scores on this benchmark.
What is RepoBench?
What RepoBench measures and how its scores work.
RepoBench is a benchmark for evaluating repository-level code auto-completion systems through three interconnected tasks: RepoBench-R (retrieval of relevant code snippets across files), RepoBench-C (code completion with cross-file and in-file context), and RepoBench-P (pipeline combining retrieval and prediction). Supports Python and Java programming languages and addresses the gap in evaluating real-world, multi-file programming scenarios by providing a more complete comparison of performance in auto-completion systems.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- RepoBench
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- repobench|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about RepoBench.
Which model scores highest on RepoBench?
Codestral-22B is currently ranked first with 34.0%.
What does RepoBench measure?
RepoBench is a benchmark for evaluating repository-level code auto-completion systems through three interconnected tasks: RepoBench-R (retrieval of relevant code snippets across files), RepoBench-C (code completion with cross-file and in-file context), and RepoBench-P (pipeline combining retrieval and prediction). Supports Python and Java programming languages and addresses the gap in evaluating real-world, multi-file programming scenarios by providing a more complete comparison of performance in auto-completion systems.
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.