PRISM-Vision
2 Benchmarks
Visual Understanding & Reasoning
Frontier evaluation of multimodal vision-language models — perception under adverse conditions, forensic detection of AI-generated media, and grounded scene reasoning across real-world expert workflows.
Synthetic Video Bench · AI-Generated Video Detection
Forensic detection of AI-generated video — 60 clips (15 real + 45 synthetic from Veo3, Grok Imagine, HunyuanVideo). 5 models evaluated on VQA Accuracy, Precision, Recall, F1, and Realism Delta. All models hit 100% precision but recall is the bottleneck (4–11%).
Model Rankings
VQA Accuracy · higher = better
Scatter Plot
Full Model Comparison
| PROVIDER | MODEL | VQA ACCURACY | ACCURACY | PRECISION | RECALL | F1 SCORE | REALISM (REAL) | REALISM (SYNTHETIC) | REALISM DELTA |
|---|---|---|---|---|---|---|---|---|---|
| Qwen | Qwen2.5-VL-32B-Instruct | 31.67 | 31.67 | 100 | 11.11 | 20 | 94.6 | 94.3 | 0.3 |
| x-ai | grok-4-fast-non-reasoning | 31.67 | 31.67 | 100 | 8.89 | 16.33 | 92.8 | 91.5 | 1.3 |
| nvidia | Cosmos-Reason2-8B | 30 | 30 | 100 | 6.67 | 12.5 | 0 | 96.4 | -96.4 |
| gemini-2.5-flash | 28.33 | 28.33 | 100 | 4.44 | 8.51 | 91.7 | 89.3 | 2.4 | |
| nvidia | Cosmos-Reason1-7B | 26.67 | 26.67 | 100 | 4.44 | 8.51 | 84.3 | 79.1 | 5.2 |
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