Chatterbox TTS for RTX 50-series (Blackwell). PyTorch 2.7.1 + CUDA 12.8, 22 languages.
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Chatterbox Multilingual TTS served over an OpenAI-compatible API. Built specifically for NVIDIA RTX 50-series (Blackwell, sm_120) GPUs.
The upstream travisvn/chatterbox-tts-api:gpu image ships PyTorch 2.6.0 + CUDA 12.4,
which does not have compiled kernels for Blackwell's sm_120 compute capability.
Loading the model fails with:
RuntimeError: CUDA error: no kernel image is available for execution on the device
RuntimeError: operator torchvision::nms does not exist
This image rebuilds the stack on PyTorch 2.7.1 + CUDA 12.8, which has native sm_120 support. It's the fix I needed, published so others don't have to solve it again.
docker run --rm --gpus all \
-p 8307:4123 \
-e HF_TOKEN=your_huggingface_token \
-v chatterbox-cache:/cache \
xchaix74/chatterbox-tts-api-blackwell:latest
Synthesize:
curl -X POST http://localhost:8307/v1/audio/speech \
-H "Content-Type: application/json" \
-d '{"input": "Hello from Chatterbox", "voice": "default"}' \
-o out.wav
Health check:
curl http://localhost:8307/health
HF_TOKEN — required. Get one at https://huggingface.co/settings/tokens
(The Chatterbox model is gated; the token is needed to download weights.)DEVICE — cuda (default) or cpu/cache — Hugging Face model cache. Mount a named volume so weights
persist across container restarts (~2 GB download on first run).22 languages including: English, Malay, Arabic, Mandarin, Japanese, Korean, Hindi, Tamil, Spanish, French, German, Italian, Portuguese, Russian, and more.
Content type
Image
Digest
sha256:64e84d0a9…
Size
9.1 GB
Last updated
3 days ago
docker pull xchaix74/chatterbox-tts-api-blackwell