Catching 98.9 Out of 100 Deepfakes: What It Takes to Lead Hugging Face's Leaderboard

Voice deepfake losses are projected to hit $40B by 2027, a 6,566% jump from 2023. Modulate's velma-2 now ranks #1 on Hugging Face's Speech Deepfake Leaderboard with a 1.104% average EER across 14 datasets and 2M+ audio samples, catching 98.9 out of every 100 deepfakes. This post breaks down why the Hugging Face benchmark is the most credible public standard for detection, how Modulate's voice-native ELM architecture outperforms repurposed models from Hiya and Resemble AI, and why running detection at $0.25/hr (100x cheaper than competitors) lets fraud teams monitor entire calls instead of just the opening seconds where most checks stop today.