# Gepard 1.0 brings bilingual TTS with voice cloning

> An open, autoregressive text-to-speech model targets English and Spanish under a permissive Apache 2.0 license.

Published by The Open Weights on Jun 22, 2026. Canonical: https://theopenweights.com/news/gepard-1-0-13dp

## Key facts

- Company: nineninesix
- Model: Gepard 1.0
- Version: 1.0
- Category: Text → Speech
- Modalities: Text → Speech
- License: Apache 2.0 (Open weights, commercial use allowed)
- Architecture: Qwen3_5ForCausalLM
- Precision: BF16
- Weights size: 1.1 GB
- Languages: en, es
- Significance: minor
- Published: 2026-06-22
- Last verified: 2026-07-17
- Hugging Face: https://huggingface.co/nineninesix/gepard-1.0
- Canonical URL: https://theopenweights.com/news/gepard-1-0-13dp

A team publishing under the handle nineninesix has released [Gepard 1.0](https://huggingface.co/nineninesix/gepard-1.0), an autoregressive text-to-speech model that supports voice cloning across English and Spanish. The model arrives on Hugging Face under the permissive Apache 2.0 license, which allows both commercial and research use.

Gepard uses an autoregressive approach to generation, producing speech token by token rather than in a single pass. That design has become common in recent open TTS work, trading some efficiency for expressive, natural-sounding output and the flexibility to adapt to a target voice from a reference sample.

## Why it matters

Open speech synthesis is a fast-moving corner of the AI ecosystem, and bilingual coverage remains relatively scarce compared to English-only releases. A model that handles both English and Spanish with cloning support lowers the barrier for developers building voice assistants, dubbing tools, and accessibility features across two of the world's most widely spoken languages.

A few practical notes for anyone evaluating the release:

- **Languages:** English and Spanish
- **Capability:** voice cloning from a reference sample
- **License:** Apache 2.0, permissive for commercial use

The repository does not publish detailed benchmark figures or parameter counts, so teams will want to test Gepard against their own audio quality and latency requirements before deploying. As an initial 1.0 release, it establishes a baseline the project can build on.

## Get the model

- [Hugging Face](https://huggingface.co/nineninesix/gepard-1.0)

## Sources

- [nineninesix/gepard-1.0](https://huggingface.co/nineninesix/gepard-1.0) — Hugging Face, Jun 22, 2026

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Source: The Open Weights (https://theopenweights.com/). Aggregated and written by Claude, curated by humans. Cite as: "Gepard 1.0 brings bilingual TTS with voice cloning", The Open Weights, Jun 22, 2026, https://theopenweights.com/news/gepard-1-0-13dp