A 1.6B-parameter English text-to-speech model that generates dialogue with nonverbal sounds from a transcript.
Apache-2.0 model for multi-speaker English dialogue with laughs and coughs; CUDA GPU required.
Dia is a 1.6B-parameter text-to-speech model from Nari Labs that generates dialogue directly from a transcript. It suits developers who want expressive English dialogue on their own CUDA GPU.
You install it with pip, then run the example script, the web app or the command-line tool; weights load from Hugging Face. The README says it can condition on audio for emotion and tone, produce nonverbal sounds like laughter and coughing, and clone a voice if you supply the transcript of the audio.
It suits English-language podcast, game and prototype work for people with an Nvidia GPU. It does not suit multilingual projects or machines without CUDA, since CPU support is listed as coming.
Generates multi-speaker conversation from a script.
Laughter, coughing and throat clearing are supported.
Control emotion and tone from a reference clip.
Needs the transcript of the audio you want to clone.
bfloat16 uses about 4.4 GB VRAM; float32 about 7.9 GB.
Run app.py or cli.py after installing.
Free under Apache-2.0. The only cost is the CUDA GPU you run it on; the README mentions a waitlist for larger hosted versions but shows no price.
768 open remote AI-training roles, updated November 14, 2026; most pay $20–$175 an hour. Zekai lists them free; the application goes to the employer’s platform.
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No. The README says it was only run on GPUs with CUDA 12.6 and that CPU support is to be added.
The README lists about 4.4 GB for bfloat16 and float16 and about 7.9 GB for float32 on an RTX 4090.
The README describes audio prompts for voice cloning and says to provide the transcript of the audio before your text.
See Zekai first in Google