Agentic Coding Benchmark

Long-Horizon Terminal Bench

Category

Agentic Coding

Score type

percent

Scale

100%

higher is better

Models tested

1

What is Long-Horizon Terminal Bench?

Long-Horizon Terminal Bench is a benchmark for how well a model works as an autonomous coding agent. It was built to compare language models on a clearly defined set of tasks under the same grading rules, so scores are directly comparable between models.

What does it test?

Long-Horizon Terminal 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

How to read the score

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

Frequently asked questions

What is the Long-Horizon Terminal Bench benchmark?

Long-Horizon Terminal Bench is a benchmark for how well a model works as an autonomous coding agent. It was built to compare language models on a clearly defined set of tasks under the same grading rules, so scores are directly comparable between models.

What does Long-Horizon Terminal Bench test?

Long-Horizon Terminal 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 Long-Horizon Terminal 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. The declared maximum score of this benchmark is 100.0.

Where do I get Long-Horizon Terminal 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/long-horizon-terminal-bench/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 1 model tested

Reset
# Model Score Date Source Verified
1 MiniMax-M3
MiniMaxAI
38.5%
16.07.2026 MiniMax-M3 official evaluation metadata (LHTB leaderboard) Verified

What now?

You've seen how models score on Long-Horizon Terminal Bench — here's what to do next.