Breeze TTS 2 vs ElevenLabs: Open Source TTS Verdict

Breeze TTS 2 has emerged as the top-rated open-weight model on the Artificial Analysis text-to-speech leaderboard, surpassing ElevenLabs Eleven v3 with an Elo rating of 1215, compared to ElevenLabs' 1175. The hosted price for Breeze TTS 2 is $34 per 1M characters, while ElevenLabs charges $100 for the same. For non-commercial use, such as research, hobby projects, or personal endeavors, Breeze TTS 2 is the recommended choice due to its superior quality at a lower cost and the convenience of self-hosting without any per-character fees or audio leaving the user's machine.

However, for businesses offering paid products with customers, ElevenLabs is the preferred option due to its permissive licensing and broader language coverage, along with a more mature platform. When it comes to commercial self-hosting without negotiation, VoxCPM2 is a more suitable alternative. Breeze TTS 2's licence permits the use, modification, and redistribution of its inference code under Apache 2.0, but the model weights are restricted to research and non-commercial use only, necessitating a separate written licence from BreezeBlue for commercial use.

This distinction is crucial, as "open weights" and "open source" are not synonymous. The quality-price gap between Breeze TTS 2 and ElevenLabs is significant: Breeze TTS 2 delivers narration quality at about one-third of the hosted price of ElevenLabs and holds the top position among open-weight models on the leaderboard. However, it does not surpass ElevenLabs in all aspects.

ElevenLabs' Conversational model is only 5 Elo points behind Breeze TTS 2, and Cartesia Sonic 3.6 leads the entire board. Despite Breeze TTS 2's advantages, it still lags behind ElevenLabs in certain areas, such as voice cloning, bilingual support (English and Chinese), and the number of supported languages (50 vs. ElevenLabs' 74).

Self-hosting Breeze TTS 2 requires a GPU with at least 12 GB of memory for optimal performance, with a minimum of 7.7 GiB for eager inference. The model card and repository provide detailed hardware requirements, including the H100 fast path, which achieves under 40 ms time-to-first-audio and a real-time factor of 0.32, making it 3.1 times faster than playback.