Voxtral-4B-TTS-2603

Voxtral 4B TTS 2603 Voxtral TTS is a frontier, open-weights text-to-speech model that’s fast, instantly adaptable, and produces lifelike speech for voice agents. The model is released with BF16 weights and a set of reference voices. These voices are licensed under CC BY-NC 4, which is the license that the model inherits. For more details, see our: 🔊 Demo ✍️ Blog post 🔬 Research Paper Key Features Voxtral TTS delivers enterprise-grade text-to-speech for production voice agents, with the following capabilities: **Realistic, expressive speech** with natural prosody and emotional range across 9 major languages, with support for diverse dialects **Text-to-Speech generation** with 20 preset voices and easy adaptation to new voices **Multilingual support**: English, French, Spanish, German, Italian, Portuguese, Dutch, Arabic, and Hindi **Very low latency** with fast time-to-first-audio, plus streaming and batch inference support **24 kHz audio output** in WAV, PCM, FLAC, MP3, AAC, and Opus formats **Production-ready performance** for high-throughput, real-time voice agent workflows [!Tip] For voice customization, visit our AI Studio. Use Cases Customer support and call center infrastructure. Financial services. _-- with video demo on banking KYC voice agents._ Manufacturing and industrial operations. Public services and government. Compliance and risk. Supply chain and logistics. Automotive and in-vehicle systems. Sales and marketing. Real-time translation. [!Warning] Responsible Use - You are responsible for complying with applicable laws and avoiding misuse. Benchmark Results Measured using vllm_omni/examples/offline_inference/voxtral_tts/end2end.py. Input: 500-character text with a 10-second audio reference. Hardware: single NVIDIA H200. vllm version: v0.18.0. Note*: The RTF in `end2end.py` uses an inverted formula (higher = better). The table below converts it back to the standard RTF convention (lower = better) | Concurrency | Latency | RTF | Throughput (char/s/GPU) |