Benchmark Almanac

TUA-Bench

Claude Opus 4.8 65.8% leads since June 2026
Not in model cards

Agents use a terminal for general computer tasks beyond coding, such as file, system and everyday productivity work.

49 upvotes on Hugging Face papers.

Made by
Meta
Released
June 2026
Kind
Terminal tasks
Level
Everyday
Scored
Checked automatically
Answers
Agent task
Tasks
All public
Strongest model tested
GPT-5.5 #20 on the capability index
Last model added
June 2026
Scores refreshed
November 12th, 2026

In the authors’ words

As large language models and harness frameworks continue to advance, agents operating in terminals are increasingly capable of performing a broader range of general computer-use tasks beyond coding. However, existing benchmarks do not adequately evaluate general-purpose terminal computer-use agents (TUAs): general computer-use benchmarks primarily target graphical user interfaces (GUIs), whereas terminal-based benchmarks largely emphasize technical and programming-centric workflows historically native to the shell. We introduce TUA-Bench, a general-purpose benchmark for terminal-use agents. TUA-Bench includes 120 real-world tasks across five task families, covering routine digital activities-including document editing, email management, and live-web information seeking-as well as scientific and engineering workflows co-designed with PhD-level domain experts that require specialized software. This breadth distinguishes TUA-Bench from prior shell-focused or domain-specific benchmarks. Each task is manually designed, runs in a real terminal with a deterministic setup script, and is evaluated by an execution-based scoring protocol. We find that the strongest frontier agent, Claude Code with Claude Opus 4.8 max reasoning effort, achieves 65.8% overall performance, with substantial gaps across both tracks. By providing a broad and realistic evaluation of terminal-use capabilities, TUA-Bench aims to accelerate the transition from narrow, task-specific assistants to general-purpose agents capable of operating reliably across diverse digital environments.

Abstract of TUA-Bench: A Benchmark for General-Purpose Terminal-Use Agents (arXiv:2606.28480, CC0)
12
Models scored on its own leaderboard

Claude Opus 4.8 leads with 65.8% among models released by June 2026

Best score per model from the benchmark's own leaderboard, read on November 12th, 2026. Where a model ran with several settings or harnesses, we keep its best. Every run is in the next chart.

The newest model with a score here came out in June 2026, and nobody has tested a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:

  1. 1 Claude Opus 4.8 max 65.8%
  2. 2 GPT-5.5 xhigh 64.7%
  3. 3 Claude Opus 4.7 max 58%
  4. 4 Gemini 3.1 Pro high 49.3%
  5. 5 GLM-5.1 xhigh 48.1%
  6. 6 MiniMax-M3 xhigh 47%
  7. 7 DeepSeek-V4-Pro xhigh 46.2%
  8. 8 Qwen3.7-Max xhigh 44.9%
  9. 9 Claude Sonnet 4.6 max 42.8%
  10. 10 Kimi K2.6 xhigh 42.8%
  11. 11 GPT-5.4 Mini xhigh 27.2%
  12. 12 Claude Haiku 4.5 none 23.9%

Source: Official TUA-Bench leaderboard

#ModelScoreSettingDateSource
1 Claude Opus 4.8 65.8% max, Claude Code May 2026 Official leaderboard
2 GPT-5.5 64.7% xhigh, Codex Apr 2026 Official leaderboard
3 Claude Opus 4.7 58% max, Terminus-2 Apr 2026 Official leaderboard
4 Gemini 3.1 Pro 49.3% high, Terminus-2 Feb 2026 Official leaderboard
5 GLM-5.1 48.1% xhigh, Terminus-2 Apr 2026 Official leaderboard
6 MiniMax-M3 47% xhigh, Terminus-2 Jun 2026 Official leaderboard
7 DeepSeek-V4-Pro 46.2% xhigh, Terminus-2 Apr 2026 Official leaderboard
8 Qwen3.7-Max 44.9% xhigh, Terminus-2 May 2026 Official leaderboard
9 Claude Sonnet 4.6 42.8% max, Terminus-2 Feb 2026 Official leaderboard
10 Kimi K2.6 42.8% xhigh, Terminus-2 Apr 2026 Official leaderboard
11 GPT-5.4 Mini 27.2% xhigh, Terminus-2 Mar 2026 Official leaderboard
12 Claude Haiku 4.5 23.9% none, Terminus-2 Oct 2025 Official leaderboard

More effort adds a median 24 points

Models the leaderboard ran at two or more effort levels. We don’t have enough cost data here to say what the extra effort costs.

Lowest effort to highest, light to dark
GPT-5.5 Codex
none low medium high
64.7%
GPT-5.5 Terminus-2
none low medium high
60.1%
Claude Opus 4.7 Terminus-2
none low medium high xhigh
58%
Claude Opus 4.7 Claude Code
none low medium high xhigh
50.3%

Source: Official TUA-Bench leaderboard

ModelEffortHarnessScoreCost per taskOutput tokens
Claude Opus 4.8 max Claude Code 65.8%
GPT-5.5 xhigh Codex 64.7%
GPT-5.5 high Codex 64.2%
Claude Opus 4.8 max OpenHands SDK 63.4%
GPT-5.5 xhigh Mini-SWE-Agent 62.4%
GPT-5.5 xhigh OpenHands SDK 61.4%
GPT-5.5 xhigh Terminus-2 60.1%
Claude Opus 4.8 max Terminus-2 59.7%
GPT-5.5 medium Codex 58.8%
Claude Opus 4.7 max Terminus-2 58%
GPT-5.5 high Terminus-2 57.8%
Claude Opus 4.8 max Mini-SWE-Agent 57.4%
Claude Opus 4.7 xhigh Terminus-2 55.4%
GPT-5.5 medium Terminus-2 51.5%
Claude Opus 4.7 xhigh Claude Code 50.3%
Claude Opus 4.7 max Claude Code 50.1%
Claude Opus 4.7 high Terminus-2 49.9%
Claude Opus 4.7 none Terminus-2 49.7%
Gemini 3.1 Pro high Terminus-2 49.3%
Gemini 3.1 Pro none Mini-SWE-Agent 48.5%
GLM-5.1 xhigh Terminus-2 48.1%
Claude Opus 4.7 high Claude Code 47.4%
MiniMax-M3 xhigh Terminus-2 47%
GPT-5.5 low Codex 46.7%
DeepSeek-V4-Pro xhigh Terminus-2 46.2%
Claude Opus 4.7 medium Terminus-2 45.7%
Claude Opus 4.7 none Claude Code 45%
Qwen3.7-Max xhigh Terminus-2 44.9%
Gemini 3.1 Pro none OpenHands SDK 44.1%
Claude Sonnet 4.6 max Terminus-2 42.8%
Kimi K2.6 xhigh Terminus-2 42.8%
GPT-5.5 low Terminus-2 42.4%
Claude Opus 4.7 medium Claude Code 41.7%
Claude Opus 4.7 low Terminus-2 41.2%
GPT-5.5 none Terminus-2 36.5%
Claude Opus 4.7 low Claude Code 35.3%
GPT-5.5 none Codex 35%
GPT-5.4 Mini xhigh Terminus-2 27.2%
Claude Haiku 4.5 none Terminus-2 23.9%

Number one over time

Lab claims count from the day the card came out, independent runs from the model’s release.

Anthropic
Own leaderboard Not tested since Jun 2026

Source: Official TUA-Bench leaderboard

Scores over time

All the scores we have, one dot each, so a model tested at several settings appears more than once.

On the benchmark’s own leaderboard Best so far
0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) Claude Opus 4.8 Claude Opus 4.7 Gemini 3.1 Pro Claude Sonnet 4.6 Claude Haiku 4.5 0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) Claude Opus 4.8 Claude Opus 4.7

Source: Official TUA-Bench leaderboard

No lab model card reports it yet

We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark.

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  • Harbor-Index In use Agents solve about 80 hard tasks drawn from 29 benchmarks run through Harbor adapters, such as HLE, GSO and SWE-bench Pro. Each task keeps its source verifier. GPT-5.5 28.1%
  • Terminal-Bench 2.1 Extended Not in model cards Agents complete long command-line tasks in containers, scored by verification tests. Mercor adds 99 new expert-written tasks to the 89 public ones and reports both scores. Muse Wonder 54%
  • Terminal-Bench 4.1 Not in model cards The Terminal-Bench 4.0 tasks with hardened verifiers: agents complete 66 hard tasks in containerized terminals across software, ML, science, security, and operations. Test scripts verify each result, scored as resolution rate. Claude Opus 5.5 65.8%
  • o11y-bench Not in model cards Agents query metrics, logs and traces in a live Grafana stack, investigate incidents and fix dashboards. Grading checks claims against facts read from the same environment. Claude Opus 5.5 93.8%