NL2Repo-Bench

NL2Repo-Bench is a benchmark for how well a model works as an autonomous coding agent. The official description says: "NL2Repo-Bench - repository generation from natural language". Below we describe in simple words what benchmarks of this type generally examine.

NL2Repo-Bench measures how well a model works as an autonomous coding agent. In detail, it checks:

• fixing real, open bugs from real software repositories
• planning multi-step changes, running commands and editing files by itself
• passing the project's test suite after its changes
• handling whole repositories, not just small isolated code snippets

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.

Official methodology note: NL2Repo-Bench - repository generation from natural language. Evaluated with Claude Code harness. Bash commands that access the specific repository are disabled to prevent reward hacking.

What is the NL2Repo-Bench benchmark?

NL2Repo-Bench is a benchmark for how well a model works as an autonomous coding agent. The official description says: 'NL2Repo-Bench - repository generation from natural language'. Below we describe in simple words what benchmarks of this type generally examine.

What does NL2Repo-Bench test?

NL2Repo-Bench mainly measures how well a model works as an autonomous coding agent. Concretely, it checks: fixing real, open bugs from real software repositories; planning multi-step changes, running commands and editing files by itself; passing the project's test suite after its changes.

How is the NL2Repo-Bench score calculated?

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.

Where do I get NL2Repo-Bench data and scores?

The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/nl2repo-bench/scores) or pull it directly from the Open LLM Radar API with any HTTP client.