Benchmark Almanac

OSWorld 2.0

Claude Opus 4.8 20.6% leads since Jun 2026 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.

Releases are versioned and some cards report the offline subset or partial score, so cross-card numbers are not directly comparable.

In the authors’ words

Existing computer-use benchmarks fail to capture the realism, complexity, and long-horizon demands of real-world computer use, limiting their ability to reveal the limitations of frontier agents. We introduce OSWorld 2.0, a benchmark of 108 long-horizon computer-use workflows across everyday and professional tasks, designed to capture complex and challenging real-world phenomena. Each task represents a realistic end-to-end workflow that takes human users a median of about 1.6 hours to complete and requires an average of 318 tool calls with Claude Opus 4.7 using maximum thinking, compared with about 30 in OSWorld 1.0. OSWorld 2.0 targets challenge phenomena that are common in real workflows yet underrepresented in prior benchmarks, spanning interaction-design challenges such as streaming interaction and dynamic environments, as well as agent-pattern challenges such as cross-source reasoning, implicit-state inference, and visual-spatial precision. Tasks are grounded in authentic input artifacts and cross-referenced against realistic stateful user profile data, and include separate safety reports auditing safety-sensitive execution. Under our primary binary-completion metric at 500 steps, Claude Opus 4.8 with maximum thinking and batched tool calls scores best but still completes only 20.6% of tasks at a 54.8% partial score; GPT-5.5 is far more token-efficient yet plateaus near 13%. These results show that current agents are still far from professional-level computer use: rather than stumbling on basic GUI control or coding, they lose track of constraints, miss information that arrives mid-task, guess rather than ask the user, and skip verification, struggling most when a task hinges on hidden state they must recover.

Abstract of OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks (arXiv:2606.29537, CC0)
Made by XLANG Lab , HKU Released Jun 2026 Desktop apps All tasks public Last in a launch post Oct 2026 Last model added Oct 2026 Scores refreshed 2 Nov 2026
Level
University Undergraduates and entry-level professionals
Scored
Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
Answers
Agent task Many steps in a terminal, browser, desktop, app, game or robot.
7
Models scored on its own leaderboard
18
Launch posts list it, from 8 labs
6
System cards report it, from 4 labs

Claude Opus 4.8 leads with 20.6% among models released by Jun 2026

Best score per model from the benchmark's own leaderboard, read on 2 Nov 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 Jun 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 20.6%
  2. 2 Claude Opus 4.7 max 18.2%
  3. 3 GPT-5.5 xhigh, 150 steps 13%
  4. 4 Claude Sonnet 4.6 medium 9.30%
  5. 5 Kimi K2.6 enabled, 300 steps 4.60%
  6. 6 MiniMax-M3 enabled 4.60%
  7. 7 Qwen3.7-Plus thinking 2.80%
#ModelScoreSettingDateSource
1 Claude Opus 4.8 20.6% max, batched tool May 2026 Official leaderboard
2 Claude Opus 4.7 18.2% max, batched tool Apr 2026 Official leaderboard
3 GPT-5.5 13% xhigh, 150 steps, batch tool Apr 2026 Official leaderboard
4 Claude Sonnet 4.6 9.30% medium, standard Feb 2026 Official leaderboard
5 Kimi K2.6 4.60% enabled, 300 steps, standard Apr 2026 Official leaderboard
6 MiniMax-M3 4.60% enabled, standard Jun 2026 Official leaderboard
7 Qwen3.7-Plus 2.80% thinking, standard Jun 2026 Official leaderboard

Epoch AI has scores for 9 models. Labs report scores for 19 models in their cards. We plot every source in the charts below.

Of runs with a cost, the best scores 13.9% for $36 a task

Runs on the cost frontier score higher than any run that's cheaper. Claude Sonnet 4.6 at medium comes within 4.6 points of the best for $14 a task, about half the cost. The costs are the leaderboard's own estimates, so compare them only within this benchmark.

Anthropic OpenAI MiniMax Cost frontier One model at each effort level
0% 5% 10% 15% $0.10 $1.00 $10 $100 Cost per task, log scale Claude Opus 4.7, max GPT-5.5, xhigh, 150 steps Claude Sonnet 4.6, medium Claude Sonnet 4.6, medium, 300 steps MiniMax-M3, enabled MiniMax-M3, enabled, 300 steps MiniMax-M3, enabled, 150 steps 0% 5% 10% 15% $0.10 $1.00 $10 $100 Cost per task, log scale Claude Opus 4.7, max GPT-5.5, xhigh, 150 steps
ModelEffortHarnessScoreCost per taskOutput tokens
Claude Opus 4.8 max batched tool 20.6%
Claude Opus 4.8 max standard 18.5%
Claude Opus 4.7 max batched tool 18.2%
Claude Opus 4.7 max standard 13.9% $36
Claude Opus 4.7 max, 300 steps standard 13% $23
GPT-5.5 xhigh, 150 steps batch tool 13% $17
GPT-5.5 xhigh, 300 steps batch tool 13% $25
GPT-5.5 xhigh batch tool 13% $25
Claude Sonnet 4.6 medium standard 9.30% $14
Claude Sonnet 4.6 medium, 300 steps standard 8.30% $9.17
Claude Sonnet 4.6 max standard 8.30% $22
Claude Sonnet 4.6 max, 300 steps standard 6.50% $16
Claude Sonnet 4.6 medium, 150 steps standard 4.60% $3.80
Claude Sonnet 4.6 max, 150 steps standard 4.60% $7.41
Claude Opus 4.7 max, 150 steps standard 4.60% $9.54
Kimi K2.6 enabled, 300 steps standard 4.60% $5.59
Kimi K2.6 enabled standard 4.60% $6.56
MiniMax-M3 enabled standard 4.60% $2.40
MiniMax-M3 enabled, 300 steps standard 3.70% $1.69
Qwen3.7-Plus thinking standard 2.80% $3.81
Kimi K2.6 enabled, 150 steps standard 1.90% $3.11
MiniMax-M3 enabled, 150 steps standard 1.90% $0.80
Qwen3.7-Plus thinking, 300 steps standard 1.90% $3.73

Number one over time

Lab claims count from the day the card came out, independent runs from the model’s release. We draw one row each for the benchmark’s own leaderboard, Epoch AI’s runs and what labs claim in their cards.

Anthropic OpenAI
Own leaderboard Replaced by 2.0 Aug, Aug 2026
Epoch AI runs Replaced by 2.0 Aug, Aug 2026
Lab claims 3 leaders

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 Run or collected by Epoch AI Reported by the lab in its model card Best so far
0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) Claude Fable 5.1 Claude Opus 5 GPT-5.6 Sol Claude Opus 4.8 Claude Sonnet 4.6 0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) Claude Fable 5.1 Claude Opus 5

8 labs put it in a launch post in the last six months

Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.

OpenAI
Moonshot AI
Anthropic
Qwen
Google DeepMind
Z.ai
Meta
MiniMax
DateLaunch postScoreAs the post writes it
19 Oct 2026 MiniMax-M3.1-Flash 61.7 OSWorld 2.0
13 Oct 2026 Gemini 4 Argon 69.2 OSWorld-2.0 (Offline subset, Partial score)
29 Sep 2026 GPT-6.1 Sol 71.4 OSWorld 2.0, offline set, partial reward (GPT-6.1 Sol Max)
22 Sep 2026 GPT-6 Luna 52.7 OSWorld 2.0, offline set (GPT-6 Luna max)
22 Sep 2026 GPT-6 Sol 64.4 OSWorld 2.0, offline set, partial reward (GPT-6 Sol max)
3 Sep 2026 GPT-6 Astra 72.6 OSWorld 2.0 (v2026.08.08, offline set, partial score)
2 Sep 2026 Muse Spark 1.3 66.9 OSWorld 2.0 (Agentic computer use) partial 66.9 / binary 32.0
2 Sep 2026 Gemini 3.8 Flash 59 OSWorld-2.0 (Partial score, batch tool enabled)
1 Sep 2026 Claude Fable 5.1 77.9 Computer use OSWorld 2.0 (partial)
26 Aug 2026 Qwen3.8 Flash 19.4 Computer use OSWorld 2.0 Binary 19.4 Partial 52.3
26 Aug 2026 GLM-5.3-Flash 59.1 OSWorld 2.0
13 Aug 2026 Gemini 3.7 Flash 47.9 OSWorld-2.0
3 Aug 2026 Qwen 3.8 Max 19.4 OSWorld 2.0 (binary / partial) 19.4 / 46.7
24 Jul 2026 Claude Opus 5 70.6 Computer use OSWorld 2.0
16 Jul 2026 Kimi K3 58.3 OSWorld 2.0
9 Jul 2026 GPT-5.6 Luna 45.6 OSWorld 2.0
9 Jul 2026 GPT-5.6 Terra 50.2 OSWorld 2.0
9 Jul 2026 GPT-5.6 Sol 62.6 OSWorld 2.0 (Sol, max)

6 system cards report it, from 4 labs

Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.

DateDocumentScoreAs the document writes itSection
13 Oct 2026 Gemini 4 Argon model card 69.2 OSWorld-2.0, offline subset, partial score (results table, p.5) Capabilities
2 Sep 2026 Gemini 3.8 Flash model card 59 OSWorld-2.0, partial score, batch tool enabled (results table, p.5) Capabilities
13 Aug 2026 Gemini 3.7 Flash model card 47.9 OSWorld-2.0 (results table, p.5) Capabilities
27 Jul 2026 Kimi K3 technical report 58.3 OSWorld 2.0 (Table 2) Capabilities
24 Jul 2026 Claude Opus 5 system card 70.6 OSWorld 2.0, first-attempt success rate averaged over five runs, 70.57% in 8.12.3 (Table 8.1.A) Capabilities
9 Jul 2026 Muse Spark 1.1 system card 47.3 OSWorld 2.0 partial score, w/o exec (Figure 44). Binary = 14.2 Capabilities

Versions

We switch the top row to each new version when it comes out. Open it for one row per version. An old version stays in play while people still test it, so whoever first takes it past 85% gets credit for closing it out.

Qwen Anthropic OpenAI ByteDance Seed
OSWorld 2.1 25 leaders
OSWorld Not tested since Jun 2026
Seed2.1 Pro 78.8%
OSWorld-Verified Passed 85% in Jun 2026, by Claude Fable 5
Qwen 3.8 Max 86.1%
OSWorld 2.0 4 leaders
OSWorld 2.0 (Aug 2026) Replaced by 2.1, Sep 2026
OSWorld 2.1 2 leaders

More in Computer and browser use

All 56 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%
  • 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. Kimi K3 74.4%
  • RecreationBench In use Agents explore a running reference app and rebuild it, across 250 tasks on five platforms. Programmatic tests and a VLM judge score the result. GPT-6 Astra 58.1%