WeaveBench
Computer-use agents do 114 long tasks in 8 work domains that mix GUI actions with command-line and code operations in one trajectory. Results are checked against verifiable artifacts.
EMNLP 2026. 55 HF paper upvotes.
- Made by
- Microsoft and collaborators
- Released
- June 2026
- Kind
- Desktop apps
- Level
- Expert
- 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
Computer-use agents (CUAs) increasingly operate in runtimes that combine visual desktop control, command-line execution, code editing, browsers, and external tools. Existing benchmarks, however, often evaluate these interfaces as separable capabilities, leaving long-horizon cross-interface orchestration under-tested. Thus, we introduce WeaveBench, a long-horizon hybrid-interface benchmark with 114 tasks across 8 real-world work domains, grounded in real user requests and publicly verifiable artifacts. Each task requires agents to combine GUI observations/actions with CLI/code operations within a single trajectory. We evaluate these tasks on a real Ubuntu desktop inside deployed CLI-agent runtimes, augmented with a minimal desktop-control plugin. We also propose a companion trajectory-aware judge that inspects deliverables, files, screenshots, logs, and action traces, while detecting shortcut behaviors such as fabricated visual evidence or hard-coded metrics. Across frontier model-runtime pairings, the best PassRate reaches only 41.2%, showing the benchmark remains far from saturated. The trajectory-aware judge further reveals that outcome-only grading substantially overestimates agent performance. Overall, WeaveBench exposes a critical gap in CUA evaluation and provides an effective testbed to measure whether agents can orchestrate GUI, CLI, and code operations across long-horizon real-world tasks.
Claude Opus 4.7 leads with 41.2% among models released by June 2026
Best score per entry from the benchmark's own leaderboard, read on November 12th, 2026. Where a model ran with several settings or harnesses, we keep its best. Names in gray aren't in our model list: fine-tunes, agent systems, products and older models. They don't count toward leaders.
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 4.7 41.2%
- 2 GPT-5.5 35.1%
- 3
Seed2.1 Pro 30.7%
- 4 Seed 2.1 turbo 28.9%
- 5 GPT-5.4 22.8%
- 6 GPT-5.3 Codex 18.4%
- 7 GPT-5.2 Codex 6.10%
- 8 GPT-5.1-Codex 1.80%
- 9
Gemini 3.1 Pro 1.80%
- 10 Qwen3-VL-8B-Think 0.90%
- 11
Qwen3.5 397B-A17B 0.90%
- 12 GUI-Owl-1.5-32B 0%
Source: Official WeaveBench leaderboard
| # | Entry | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | Claude Opus 4.7 | 41.2% | Claude Code | Apr 2026 | Official leaderboard |
| 2 | GPT-5.5 | 35.1% | Codex CLI | Apr 2026 | Official leaderboard |
| 3 | | 30.7% | Claude Code | Jun 2026 | Official leaderboard |
| 4 | Seed 2.1 turbo | 28.9% | Claude Code | Official leaderboard | |
| 5 | GPT-5.4 | 22.8% | OpenClaw | Mar 2026 | Official leaderboard |
| 6 | GPT-5.3 Codex | 18.4% | OpenClaw | Feb 2026 | Official leaderboard |
| 7 | GPT-5.2 Codex | 6.10% | OpenClaw | Dec 2025 | Official leaderboard |
| 8 | GPT-5.1-Codex | 1.80% | OpenClaw | Nov 2025 | Official leaderboard |
| 9 | | 1.80% | OpenClaw | Feb 2026 | Official leaderboard |
| 10 | Qwen3-VL-8B-Think | 0.90% | OpenClaw | Official leaderboard | |
| 11 | | 0.90% | OpenClaw | Feb 2026 | Official leaderboard |
| 12 | GUI-Owl-1.5-32B | 0% | OpenClaw | Official leaderboard |
Number one over time
Lab claims count from the day the card came out, independent runs from the model’s release.
Source: Official WeaveBench 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 WeaveBench 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.
More in Computer and browser use
- BrowseComp In use Hard-to-find facts that need persistent web browsing. Short verifiable answers graded for exact correctness. Claude Fable 5 93.3%
- ScreenSpot-Pro In use GUI grounding on high-resolution professional-software screenshots. The model must locate the target UI element. GPT-6 Astra 92.7%
- AndroidWorld In use Agents complete 116 tasks across 20 real Android apps in an emulator. Each task checks the device's system state to judge success. GPT-6 Astra 100%
- OSWorld 2.1 In use Agents complete 108 long-horizon workflows across 31 self-hosted websites and desktop apps, averaging 318 tool calls. Scored by binary completion and checkpoint partial credit. Claude Opus 5.5 81.8%
- WebArena-Verified In use Agents complete 812 audited WebArena tasks on self-hosted websites. Deterministic evaluators check the agent's answer and captured network traces.
Muse Spark 1.1 69%
- MobileWorld In use Agents complete 201 tasks across 20 mobile apps, including tasks that need user clarification or MCP tools. Backend checks verify success. GPT-5 55.3%