SceneActBench - Dynamic: leaderboard
Metric: Task score (0-100): 10 low-poly Kenney scenes from a sampled 144-frame video: place and keyframe every mover, scored by mean motion and layout error against unit references; every configuration drives one headless Blender through the same MCP tool interface (scene and object inspection, Python execution, rendering) with task step budgets; each native geometric error or F-score is mapped to a 0 to 100 case score against a fixed reference, invalid outputs score 0, cases are averaged per task. Source: arxiv.org. Saturation forecast: Around August 2028. 11 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Seed 2.0 Pro (High) | 70.7 |
| 2 | GPT-5.4 (Medium) | 68.5 |
| 3 | Gemini 3.1 Pro (Preview) (High) | 63.9 |
| 4 | Claude Opus 4.6 (High) | 63.2 |
| 5 | Step 3.7 Flash (High) | 57.9 |
| 6 | Claude Sonnet 5 (High) | 49.9 |
| 7 | GPT-5.4 (High) | 46.7 |
| 8 | Kimi K2.6 (Thinking) | 44.8 |
| 9 | MiniMax M3 (High) | 41.4 |
Interactive version: theaggregate.ai/benchmark?slug=sceneactbench-dynamic · How It Works · Data refreshed daily, snapshot 2026-09-29.