OmniaBench - DAG: leaderboard

Multi-turn tasks in which an agent works through a sampled chain of dependent tool calls in a stateful simulated environment while a simulated user reveals requirements; from OmniaBench (2026). Pass@1 in percent, a task counts only if every rubric item is met; higher is better.

Metric: Pass@1 (%; 354 multi-turn stateful tasks built from sampled tool-dependency graphs, one per level-2 domain, with a simulated user; a task counts as solved only when every rubric item is satisfied (Program tasks by a VerifyCode check); up to 200 tool-call steps; challenging set of 644 tasks evaluated June 29 to July 15, 2026). Source: arxiv.org. Saturation forecast: Around September 2027. 22 models tracked.

Top models

#ModelScoreOverall rank
1Claude Sonnet 5 (Max)57.34#111 (Claude Sonnet 5)
2GPT-5.6 Sol (High)55.37#30 (GPT-5.6 Sol)
3GLM-5.2 (Max)54.8#138 (GLM-5.2)
4GPT-5.5 (High)54.8#49 (GPT-5.5)
5Gemini 3.5 Flash (High)54.24#101 (Gemini 3.5 Flash)
6Claude Opus 4.7 (Max)53.39#79 (Claude Opus 4.7)
7DeepSeek V4 Pro (Max)52.54#188 (DeepSeek V4 Pro)
8DeepSeek V4 Flash (Max)51.13#258 (DeepSeek V4 Flash)
9GLM-5 (Thinking)50.85#260 (GLM-5)
10Qwen 3.5 397B A17B50.56#246
11Gemini 3.1 Pro (Preview)50.28#94
12Kimi K2.6 (Thinking)49.72#178 (Kimi K2.6)
13Qwen 3.7 Max (Thinking)48.59#145 (Qwen 3.7 Max)
14Qwen 3.6 27B48.02#341
15Qwen 3.6 35B A3B43.22#462

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=omniabench-dag · How It Works · Data refreshed daily, snapshot 2026-11-13.