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Choose the appropriate GPU according to the XTTS-v2 model size(2GB).
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When deploying XTTS models like XTTS-v2 or XTTS-v1 from Hugging Face, GPU selection significantly impacts performance, especially for voice cloning and real-time inference. Entry-level GPUs like the GTX 1650 and GTX 1660 can run the models with slower inference speeds and are suitable for testing or offline batch generation. Mid-tier cards like RTX 3060 Ti and NVIDIA A4000 strike a great balance between cost and capability.
|
Model Name
|
Size (4-bit Quantization)
|
Recommended GPUs
|
|---|---|---|
| coqui/XTTS-v2 | 2 GB | GTX1650 < GTX1660 < RTX2060 < RTX4060 < GTX3060ti = A4000 < V100 |
| coqui/XTTS-v1 | 3 GB | GTX1650 < GTX1660 < RTX2060 < RTX4060 < GTX3060ti = A4000 < V100 |
Generate speech in multiple languages with consistent voice across languages—ideal for global applications.
Clone a speaker's voice using just a few seconds of audio, then synthesize speech in different languages with the same vocal identity.
Optimized for fast startup and deployment on mid-tier GPU or even CPU servers, making it highly cost-efficient.
Run the model on your own infrastructure to maintain full control of your data and voice models—no third-party dependencies.
Supports low-latency generation for real-time applications like chatbots, voice assistants, and streaming TTS services.
No licensing fees or restrictions—customize and scale the model as needed for research or commercial use.
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