LLM Reference
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AutomationBench

Metric: Accuracy (higher is better)Introduced: 2026

Multi-step computer automation and workflow-completion benchmark for agentic UI tasks. High benchmark score alone doesn't make a model the right pick — weigh it against pricing, API availability, and release date.

Models ranked

3

tracked on this benchmark

Score band

30.8 – 12.9

best → lowest tracked

Snapshot trend

+15.65

Jun 9 → Jul 16 · 1 models

Leaderboard

Tracked models ranked by Accuracy (higher is better).

Compare candidates
#Model variant and provenanceScore
1
Kimi K3
Version: 600-task public subset; official GitHub setup; max reasoning effortHarness: Not recordedEvaluator: Not recordedObserved: Jul 16, 2026Confidence: Not recordedSource

Notes: Model variant: Kimi K3 (max reasoning effort). Benchmark variant: AutomationBench 600-task public subset. Harness/evaluator: official AutomationBench GitHub setup; evaluator not disclosed by Moonshot. Source posture: Moonshot/Kimi self-reported launch table; confidence: medium because the value is vendor-reported and not independently reproduced. Recommended seed value: 30.8.

30.8
2
Claude Fable 5
Version: AutomationBenchHarness: Not recordedEvaluator: Not recordedObserved: Jun 9, 2026Confidence: Not recordedSource

Notes: DAT-6106: Unstarred in Anthropic's shared Fable 5/Mythos 5 launch table, so this is a Claude Fable 5 score.

17.4
3
GPT-5.5
Version: AutomationBenchHarness: Not recordedEvaluator: Not recordedObserved: Jun 9, 2026Confidence: Not recordedSource

Notes: DAT-6106: GPT-5.5 score from Anthropic's Fable 5 comparison table.

12.9

How to read this benchmark

This benchmark scores models where higher is better. Scores are useful for directional filtering and shortlisting — not for universal quality ranking. Prefer benchmarks closest to your workload, then validate the linked model pages for pricing, context window, and provider availability.

Trust this score when

  • There is a fresh timestamped snapshot (or multiple snapshots) for this benchmark.
  • The model list covers the same version family you can actually deploy today.
  • Top candidates overlap with your required routing and feature requirements.

Be cautious when

  • There is only one benchmark snapshot or the dataset appears stale.
  • The benchmark metric direction is opposite of your decision objective.
  • The score difference between options is narrow and likely within implementation variance.

FAQ

What does the AutomationBench benchmark measure?

Multi-step computer automation and workflow-completion benchmark for agentic UI tasks. On this page it lists 3 tracked model variants where higher is better.

Is a higher AutomationBench score always better?

For this benchmark, higher is better. A high score helps you shortlist, but confirm pricing, context window, and provider availability on each model page before committing — the top scorer is not always the right pick for your workload or budget.

How current is this AutomationBench data?

This benchmark was last reviewed on Jun 15, 2026. The tracked score average moved +15.65 points across the last 2 snapshots.

Related benchmarks

Last reviewed: Jun 15, 2026

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