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Dia-1.6B

nari-labs

Dia is a 1.6B parameter text to speech model created by Nari Labs. It was pushed to the Hub using the PytorchModelHubMixin integration. Dia **directly generates highly realistic dialogue from a transcript**. You can condition the output on audio, enabling emotion and tone control. The model can also produce nonverbal communications like laughter, coughing, clearing throat, etc. To accelerate research, we are providing access to pretrained model checkpoints and inference code. The model weights are hosted on Hugging Face. The model only supports English generation at the moment.

Speech synthesis
Input Text→ Output Audio
Price not verifiedCheck multimodal and channel pricing separately
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Dia-1.6B-0626

nari-labs

Dia is a 1.6B parameter text to speech model created by Nari Labs. It was pushed to the Hub using the PytorchModelHubMixin integration. Dia **directly generates highly realistic dialogue from a transcript**. You can condition the output on audio, enabling emotion and tone control. The model can also produce nonverbal communications like laughter, coughing, clearing throat, etc. To accelerate research, we are providing access to pretrained model checkpoints and inference code. The model weights are hosted on Hugging Face. The model only supports English generation at the moment.

Speech synthesis
Input Text→ Output Audio
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
Source / docs ↗

Dia2-2B

nari-labs

The model does not need the entire text to produce the audio, and can start generating as the first few words are given as input. You can condition the output on audio, enabling natural conversations in realtime. We provide model checkpoints (1B, 2B) and inference code to accelerate research. The model only supports up to 2 minutes of generation in English. > **Requirement** — install uv and use CUDA 12.8+ > drivers. All commands below run through `uv run …` as a rule.

Speech synthesis
Input Text→ Output Audio
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
Source / docs ↗
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Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.

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