Reproducible H100 benchmark of eager PyTorch, vLLM 0.17.1 and TensorRT-LLM on the autoregressive backbone of a multi-stage TTS model. vLLM reaches about 453 tok/s against 213 for TensorRT-LLM and 21 for eager, but the LLM is only about 21% of end-to-end latency; the flow-matching stage takes about 68%, which these engines do not cover.

Open-weight TTS and ASR run as a production-style AWS service: Kokoro-82M text-to-speech on ECS Fargate (Graviton), a CPU Whisper transcription endpoint, infrastructure in AWS CDK, keyless OIDC CI/CD, and a GPU LoRA fine-tuning track.