Matches or beats ElevenLabs Flash on prosody naturalness. 3-second voice cloning from a reference clip with no fine-tuning required. The top locally-run TTS for podcast production, audiobooks, and voice-over automation.
This model requires a specialized High-VRAM environment. Ensure you have the latest CUDA Drivers or Metal Framework installed.
Minimum VRAM: 10GB VRAM Recommended
The Voxtral TTS model by Mistral AI is a 7B parameter architecture optimized for audio tasks. It requires approximately 8GB of VRAM to comfortably run locally using a Q4_K_M quantization. Extending the context window up to 0 tokens will dynamically allocate further VRAM, meaning high-bandwidth memory hardware is strictly advised.
For running Voxtral TTS at maximum tokens-per-second, we recommend using LM Studio or Ollama with a GGUF quantization (Q4_K_M or Q6_K). If you are multi-GPU, use vLLM to distribute the layers across your VRAM pool for optimal throughput.
You will need a GPU with at least 10GB of VRAM to run the Q4_K_M quantized version smoothly with a moderate context window.
The simplest method is utilizing Ollama by executing 'ollama run voxtral' directly in your command line. Alternatively, you can search for the model via LM Studio's interface.