Zyphra/ZONOS2-GGUF
text-to-speech model by Zyphra
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Model card & documentation
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GGUF weights for Zyphra/ZONOS2, ready to run with zonos2.cpp — a standalone ggml/GGUF C++ port of ZONOS2. The entire pipeline (ECAPA speaker encoder → MoE backbone → DAC vocoder) runs as native C++ linking only libggml + gguf: no Python, no PyTorch, no CUDA-only kernels at inference time. CPU and CUDA use the same files. ZONOS2 is Zyphra's latest text-to-speech model, trained on more than 6 million hours of varied multilingual speech, delivering expressiveness and quality on par with—or even surpassing—top TTS providers at low latency with MoE. ZONOS2 excels at high-fidelity and naturalistic voice cloning. For model details and speech samples, check out our blog. A hosted version is available at cloud.zyphra.com/audio-playground. Language support is as follows. All quants keep the spine (attention + router + embeddings + speaker projection) at F16 and quantize only the MoE expert matrices — the layout that holds quality far below the usual…
Read the full model card ↗ · Preview checked 2026-10-29T06:18:46.067Z
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Model overview
Zyphra/ZONOS2-GGUF is a text-to-speech model repository published by Zyphra on Hugging Face. The source reports the gguf library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-to-speech
- Library
- gguf
- Recent downloads (30 days)
- 10,700
- Cumulative likes
- 6
- Hugging Face trending score
- 2
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-06-18T23:36:00.000Z
- Last modified
- 2026-06-22T22:19:04.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: Zyphra/ZONOS2
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-13T06:42:59.084Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.