Open TTS Leaderboard ranks multilingual and voice cloning models using objective metrics

Hugging Face released the Open TTS Leaderboard, which evaluates open-source text-to-speech models using objective metrics instead of arena-style human votes.

It measures intelligibility via WER and CER using Qwen3 ASR, speed via RTFx and time-to-first-audio on an H200 GPU, and speaker similarity via WavLM embeddings.

The leaderboard covers multilingual results and voice cloning, and it is intended to complement, not replace, human preference rankings.