nari-labs/dia

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

19378 stars · 1689 forks observed · 2026-08-28

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

Dia is a 1.6B-parameter open-weight text-to-speech model from Nari Labs that generates ultra-realistic multi-speaker dialogue in a single pass, with conditioning on audio for emotion and tone control. It ships with inference code and pretrained checkpoints on Hugging Face, and supports nonverbal cues like laughter.

Use cases

• generate realistic two-speaker dialogue audio from a script
• clone a voice from an audio prompt for TTS
• add nonverbal sounds like laughter to synthesized speech
• control emotion and tone of generated speech
• build a podcast or audiobook generator
• run a local text-to-speech model with open weights

When to choose

• you need realistic conversational speech, not single-voice narration
• you want an open-weight TTS model you can self-host
• you need speaker turns and nonverbal cues in one generation

When to avoid

• you need multilingual TTS - it only supports English
• you need very short or very long utterances, which degrade quality
• you lack a GPU for inference

Facets

library · maturity active

tts machine-learning llm-inference speech-processing artificial-intelligence deep-learning python cross-platform text-to-speech open-weights dialogue-generation voice-cloning huggingface audio gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="nari-labs/dia")