ggml-org/whisper.cpp

Health v2 · maintenance only

Adoption not part of the score

53203 stars · 6097 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A high-performance C/C++ port of OpenAI's Whisper automatic speech recognition model with no external dependencies. It supports CPU, GPU (Metal, CUDA, Vulkan, ROCm), and NPU inference with quantization, running fully offline across desktop, mobile, and WebAssembly platforms.

Use cases

• transcribe audio to text offline
• run whisper on-device on iphone or android
• add speech-to-text to a c++ application
• transcribe audio on raspberry pi
• run whisper locally with gpu acceleration
• quantized speech recognition for embedded devices

When to choose

• you need fast, dependency-free, offline speech-to-text in C/C++ or via bindings
• you want on-device transcription on mobile, desktop, or embedded hardware
• you need GPU or NPU acceleration with quantization for low resource usage

When to avoid

• you want a simple Python API and don't care about performance or dependencies (use openai/whisper or faster-whisper)
• you need speaker diarization or full audio pipeline features beyond transcription
• you need training or fine-tuning of Whisper models

Facets

library · maturity stable

speech-recognition llm-inference machine-learning speech-processing machine-learning windows wasm cpp cross-platform whisper asr speech-to-text on-device-inference quantization ggml offline-transcription natural-language-processing macos linux ios android gpu

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