Agentic Coding Benchmark

Terminal-Bench 2.1 (Terminus-2)

Terminal-Bench 2.1 evaluated with Harbor/Terminus-2 framework, parser=json, temp=1.0, top_p=1.0, 128K context, 4h timeout, 32 CPU/48GB RAM, avg of 5 runs.

Category

Agentic Coding

Score type

percent

Scale

100%

higher is better

Models tested

28

What is Terminal-Bench 2.1 (Terminus-2)?

Terminal-Bench tests whether a model can operate a computer through a terminal as an agent: it gets a Linux container and has to solve hands-on tasks (installing packages, inspecting files, writing scripts) purely via shell commands within a time limit. The score is the share of tasks completed successfully, averaged over several runs.

What does it test?

Terminal-Bench 2.1 (Terminus-2) measures how well a model works as an autonomous coding agent. In detail, it checks:

  • planning and executing multi-step shell workflows
  • installing, configuring and debugging software in a container
  • handling timeouts and failing commands
  • finishing the task within the given compute and time budget

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 Terminal-Bench 2.1 (Terminus-2) benchmark?

Terminal-Bench tests whether a model can operate a computer through a terminal as an agent: it gets a Linux container and has to solve hands-on tasks (installing packages, inspecting files, writing scripts) purely via shell commands within a time limit. The score is the share of tasks completed successfully, averaged over several runs.

What does Terminal-Bench 2.1 (Terminus-2) test?

Terminal-Bench 2.1 (Terminus-2) mainly measures how well a model works as an autonomous coding agent. Concretely, it checks: planning and executing multi-step shell workflows; installing, configuring and debugging software in a container; handling timeouts and failing commands.

How is the Terminal-Bench 2.1 (Terminus-2) 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 Terminal-Bench 2.1 (Terminus-2) data and scores?

The official source is https://artificialanalysis.ai/evaluations/terminalbench-v2-1. 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/terminal-bench-2-1-terminus-2/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 28 models tested

Reset
# Model Score Date Source Verified
26 Gemma-4-31B
Google
42.1%
19.08.2026 Report Unverified
27 Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
41.4%
25.06.2026 DeepReinforce Team (official model card - comparison) Unverified
28 Gemma4-12B
Google
21%
25.06.2026 DeepReinforce Team (official model card - comparison) Unverified
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What now?

You've seen how models score on Terminal-Bench 2.1 (Terminus-2) — here's what to do next.