TUA-Bench
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.
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:
- Claude Fable 5.2
-
Gemini 4 Carbon
- GPT-6 Astra
- Claude Opus 5.5
- and 15 more
- 1 Claude Opus 4.8 max 65.8%
- 2 GPT-5.5 xhigh 64.7%
- 3 Claude Opus 4.7 max 58%
- 4
Gemini 3.1 Pro high 49.3%
- 5 GLM-5.1 xhigh 48.1%
- 6
MiniMax-M3 xhigh 47%
- 7
DeepSeek-V4-Pro xhigh 46.2%
- 8
Qwen3.7-Max xhigh 44.9%
- 9 Claude Sonnet 4.6 max 42.8%
- 10 Kimi K2.6 xhigh 42.8%
- 11 GPT-5.4 Mini xhigh 27.2%
- 12 Claude Haiku 4.5 none 23.9%
Source: Official TUA-Bench leaderboard
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 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 | | 49.3% | high, Terminus-2 | Feb 2026 | Official leaderboard |
| 5 | GLM-5.1 | 48.1% | xhigh, Terminus-2 | Apr 2026 | Official leaderboard |
| 6 | | 47% | xhigh, Terminus-2 | Jun 2026 | Official leaderboard |
| 7 | | 46.2% | xhigh, Terminus-2 | Apr 2026 | Official leaderboard |
| 8 | | 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.
Source: Official TUA-Bench leaderboard
| Model | Effort | Harness | Score | Cost per task | Output 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% | ||
| | high | Terminus-2 | 49.3% | ||
| | none | Mini-SWE-Agent | 48.5% | ||
| GLM-5.1 | xhigh | Terminus-2 | 48.1% | ||
| Claude Opus 4.7 | high | Claude Code | 47.4% | ||
| | xhigh | Terminus-2 | 47% | ||
| GPT-5.5 | low | Codex | 46.7% | ||
| | xhigh | Terminus-2 | 46.2% | ||
| Claude Opus 4.7 | medium | Terminus-2 | 45.7% | ||
| Claude Opus 4.7 | none | Claude Code | 45% | ||
| | xhigh | Terminus-2 | 44.9% | ||
| | 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.
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.
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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