MLX inference for NVIDIA PersonaPlex on Apple Silicon.
This package supports:
- Realtime local mode (
personaplex_mlx.local) - Realtime web mode (
personaplex_mlx.local_web) - Offline WAV-to-WAV mode (
personaplex_mlx.offline)
Console entrypoints are also installed: personaplex-local, personaplex-local-web, personaplex-offline.
- Apple Silicon Mac
- Python 3.12
- Hugging Face access to
nvidia/personaplex-7b-v1
Install:
pip install -e .Accept the model license:
https://huggingface.co/nvidia/personaplex-7b-v1
Set your token:
export HF_TOKEN=<your_token>Launch realtime web mode (recommended first):
python -m personaplex_mlx.local_web \
-q 4 \
--voice NATF2 \
--text-prompt "You enjoy having a good conversation."Open http://localhost:8998 in your browser.
Realtime local terminal mode:
python -m personaplex_mlx.local \
-q 4 \
--voice NATF2 \
--text-prompt "You enjoy having a good conversation."Offline inference:
python -m personaplex_mlx.offline \
--voice NATF2 \
--text-prompt "You are a wise and friendly teacher. Answer questions or provide advice in a clear and engaging way." \
--input-wav input.wav \
--output-wav output.wav \
--output-text output.json \
--seed 42424242Built-in voice IDs:
NATF0NATF1NATF2NATF3NATM0NATM1NATM2NATM3VARF0VARF1VARF2VARF3VARF4VARM0VARM1VARM2VARM3VARM4
--voice NATF2 resolves to NATF2.pt from the downloaded voices/ bundle.
- First run downloads model assets from Hugging Face.
- Local and web clients are barebone and do not include echo cancellation. Use headphones to avoid feedback.
This project is an MLX port of NVIDIA PersonaPlex for Apple Silicon.
- NVIDIA PersonaPlex repo:
https://github.com/NVIDIA/personaplex - PersonaPlex model card:
https://huggingface.co/nvidia/personaplex-7b-v1
If you use PersonaPlex in research, cite:
@misc{roy2026personaplexvoicerolecontrol,
title={PersonaPlex: Voice and Role Control for Full Duplex Conversational Speech Models},
author={Rajarshi Roy and Jonathan Raiman and Sang-gil Lee and Teodor-Dumitru Ene and Robert Kirby and Sungwon Kim and Jaehyeon Kim and Bryan Catanzaro},
year={2026},
eprint={2602.06053},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2602.06053}
}- Code: MIT (
LICENSE) - Model weights: NVIDIA Open Model License (via Hugging Face model card)