EVID-Bench - Identity Swap: leaderboard

EVID-Bench (2026) gives a multimodal model a manipulated video inside a fixed search-and-compare pipeline; it must find related source videos on the web and state what information is false. This board is point-level accuracy in percent on the 24 identity swap videos (AI generation: the identity of a person replaced by a generated one); higher is better.

Metric: Point-level accuracy (%) on the 24 identity swap videos (AI generation: the identity of a person replaced by a generated one), using the retrieval-augmented verification pipeline of the paper (chain-of-thought analysis, up to six YouTube search-verify-reflect rounds, 64 frames at 480p, temperature 0); each video has 3 to 5 annotated misinformation points, matched by a majority of three LLM judges; mean of three runs; higher is better. Source: arxiv.org. Saturation forecast: Around December 2027. 9 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.1 Pro (Preview)30.6#94
2Qwen 3.5 Plus22.2#232
3Gemini 3 Flash13.9#164
4GPT-5.511.11#49
5Claude Opus 4.68.33#102
6Qwen 3 VL 235B A22B Instruct6.9#522
7Claude Sonnet 4.65.56#161
8GPT-5.4 Mini1.39#389
9GPT-5.40#123

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

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