Reddit posts say Kyutai released three smaller Pocket TTS models, down to 1.9M parameters
AI summary
Posts on r/LocalLLaMA say Kyutai released three smaller Pocket TTS models on October 20, at 1.9M, 6.9M and 18.2M parameters. According to the same community posts, the models are English, support voice cloning and are designed to run on CPU, with the sizes switchable in a demo. The poster says the parameter counts include the audio decoder, while the reference-voice encoder is separate and only needs to be encoded once; no Kyutai statement or independent test was supplied.
In-depth insight
The poster argued that keeping speech generation on CPU leaves the GPU free for the language model, which matters when the chat model already barely fits in memory.
| Kyutai released three smaller Pocket TTS models on October 20: 1.9M, 6.9M and 18.2M parameters. These are English models, support voice cloning, and are designed to run on CPU. You can switch between the sizes in their demo here. The useful part for me is keeping speech generation on CPU and leaving the GPU to the LLM. Especially when the chat model already barely fits. Having a local assistant read its answer out loud shouldn't require another round of VRAM budgeting. I'd probably start with the 6.9M version. Getting down to 1.9M is impressive, but I'm happy to spend a few million extra parameters on a voice I can listen to for more than thirty seconds. A couple of minutes of speech with names, numbers and awkward punctuation would be a useful comparison. One detail on the size claims: those counts include the audio decoder. The encoder that processes your reference voice is separate, and the reference only needs to be encoded once. Code and setup instructions submitted by /u/BerryBlush_Rogers691 [link] [comments] |