RapidSpeech.cpp (https://github.com/RapidAI/RapidSpeech.cpp)️

RapidSpeech.cpp is a high-performance, edge-native speech intelligence framework built on top of ggml.
It aims to provide pure C++, zero-dependency, and on-device inference for large-scale ASR (Automatic Speech Recognition) and TTS (Text-to-Speech) models.

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🌟 Key Differentiators

While the open-source ecosystem already offers powerful cloud-side frameworks such as vLLM-omni, as well as mature on-device solutions like sherpa-onnx, RapidSpeech.cpp introduces a new generation of design choices focused on edge deployment.

1. vs. vLLM: Edge-first, not cloud-throughput-first

• vLLM

  • Designed for data centers and cloud environments
  • Strongly coupled with Python and CUDA
  • Maximizes GPU throughput via techniques such as PageAttention

• RapidSpeech.cpp

  • Designed specifically for edge and on-device inference
  • Optimized for low latency, low memory footprint, and lightweight deployment
  • Runs on embedded devices, mobile platforms, laptops, and even NPU-only systems
  • No Python runtime required