Human Fidelity · Text-to-Video
Elo rankings from blind votes across 3 challenges in this category.
Highlights
10 imagesBest models, by
Best Text-to-Video Models by Price
Best Text-to-Video Models by Speed
2 models waiting for enough speed data.
Best AI Models for Human Fidelity
| # | Model | Elo |
|---|---|---|
| 1 | 1236 | |
| 2 | 1229 | |
| 3 | 1220 | |
| 4 | 1217 | |
| 5 | 1211 | |
| 6 | 1175 | |
| 7 | 1148 |
Alibaba’s Wan 2.6 (1236 Elo) leads the Human Fidelity category, outperforming overall leaderboard leaders by leveraging a 60% win rate at a 64% lower price point than Kling V3 (1229 Elo). Despite its premium pricing, Kling V3 maintains the highest specific win rate at 65.4%, establishing a competitive 12-point Elo gap over ByteDance’s Seedance 2.0.
Highlighted challenges
The Rubik's Gauntlet
This prompt is one of the hardest single tests for 2026 SOTA video models because it simultaneously demands extreme fine-motor precision at high speed, long-term physical consistency (the cube must genuinely solve without morphing), and complex multi-element rendering (hyper-detailed skin, sweat, glossy reflections, and dynamic camera movement). Areas where even top models still frequently break down.
Neon Rain Reverie
This prompt is exceptionally difficult because it combines complex fluid dynamics (rain, splashing, clinging wet fabric), advanced material simulation (flowing silk + hair in wind), and atmospheric lighting; three areas where even top 2026 models still frequently produce artifacts or unrealistic behavior.
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