animation2code benchmark
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Zero-shot video (or image-frame) → code results on the test set, across commercial and open-source models.

Each output is tagged with A = appearance similarity and T = temporal similarity; higher is better for both. Click a video to inspect its code.

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model outputs

GPT-5.4

A 0.71T 0.43

Claude Sonnet 4.6

A 0.71T 0.23

LLaMA 4 Scout

A 0.57T 0.17

model outputs

GPT-5.4

A 0.61T 0.21

Claude Sonnet 4.6

A 0.78T 0.21

LLaMA 4 Scout

A 0.64T 0.00

model outputs

GPT-5.4

A 0.89T 0.14

Claude Sonnet 4.6

A 0.79T 0.15

LLaMA 4 Scout

A 0.69T 0.15

model outputs

GPT-5.4

A 0.92T 0.30

Claude Sonnet 4.6

A 0.69T 0.25

LLaMA 4 Scout

A 0.58T 0.27

model outputs

GPT-5.4

A 0.87T 0.29

Claude Sonnet 4.6

A 0.89T 0.25

LLaMA 4 Scout

A 0.69T 0.25

model outputs

GPT-5.4

A 0.79T 0.19

Claude Sonnet 4.6

A 0.85T 0.23

LLaMA 4 Scout

A 0.63T 0.19

model outputs

no output

Qwen3-VL-8B-Instruct

A T

GPT-5.4

A 0.95T 0.21

Claude Sonnet 4.6

A 0.85T 0.22

LLaMA 4 Scout

A 0.61T 0.27

model outputs

GPT-5.4

A 0.76T 0.28

Claude Sonnet 4.6

A 0.68T 0.27

LLaMA 4 Scout

A 0.49T 0.13