NVIDIA/personaplex

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10393 stars · 1449 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

PersonaPlex is a real-time, full-duplex speech-to-speech conversational model from NVIDIA that supports persona control via text role prompts and audio voice conditioning. It is built on the Moshi architecture and ships with a Python library, offline evaluation scripts, and a web server for live interaction.

Use cases

• build a real-time voice chatbot with a consistent persona
• run full-duplex speech-to-speech conversations locally on a GPU
• control the voice of a spoken AI assistant with an audio prompt
• define an assistant's role and behavior via text prompts
• evaluate conversational speech models offline with wav files
• serve a low-latency spoken dialogue model over a web UI

When to choose

• you need natural, low-latency spoken interaction with voice and role control
• you want a full-duplex model that can listen and speak simultaneously
• you have a CUDA GPU and want to self-host a conversational speech model
• you want to build on Moshi-compatible speech model weights

When to avoid

• you only need text-based chat without audio
• you have no GPU and need high-throughput production inference
• you need a managed cloud speech API rather than self-hosted weights
• you need non-English conversation support without verifying language coverage

Facets

library · maturity active

speech-recognition tts llm-inference machine-learning http-server speech-processing artificial-intelligence large-language-models chatbots python full-duplex speech-to-speech voice-cloning persona-control real-time moshi linux gpu web-server docker

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For agents

markdown · JSON · MCP: product_card(name="NVIDIA/personaplex")