# handy-computer/transcribe.cpp

ggml speech-to-text inference for 16+ model families

Repository: https://github.com/handy-computer/transcribe.cpp
Canonical: https://ross.abutalabs.com/products/transcribecpp
Homepage: https://huggingface.co/handy-computer
Language: C++
License: MIT
License Family: permissive
Topics: asr, ggml, gguf, speech-to-text
Last push: 2026-08-26T09:01:56+00:00

## Health v2 (maintenance only)
Score: 81/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 99, longevity 10
- inputs: {"age_days": 148, "days_push": 7, "days_rel": 9, "gap_med": 2.0, "n_releases_24m": 15}
- flags: young
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1836, forks 92 (observed 2026-08-28T04:05:42.610856+00:00)

## What it is
A C/C++ speech-to-text inference library built on the ggml runtime that runs 16+ ASR model families (Whisper, Parakeet, Canary, Moonshine, Qwen3-ASR, Voxtral, and more) from GGUF files. It supports streaming and batch transcription with Metal, Vulkan, and CUDA GPU backends plus an accelerated CPU path, with quantized models published and WER-verified on Hugging Face.

## Use cases
- transcribe audio files to text locally
- run whisper models without python
- streaming speech-to-text in real time
- transcribe multi-speaker audio with diarization
- run ASR on GPU with metal or cuda
- quantized speech recognition on cpu
- multilingual speech transcription offline

## When to choose
- you need fast, local speech-to-text inference in C/C++ without Python dependencies
- you want to run many different ASR model families through one unified runtime
- you need streaming transcription or speaker diarization on-device
- you want quantized GGUF models with verified WER parity to reference implementations

## When to avoid
- you need to train or fine-tune ASR models rather than run inference
- you want a managed cloud transcription API
- you need TTS or full audio-LLM features beyond transcription and translation

## Facets
- artifact type: library
- maturity: active
- function: speech-recognition, llm-inference, cli
- domain: speech-processing, machine-learning, developer-tools
- platform: cpp, windows, cross-platform
- tags: asr, ggml, gguf, whisper, parakeet, streaming-transcription, diarization, metal, vulkan, cuda, gpu, macos, linux

## Member repositories
- handy-computer/transcribe.cpp (main) score 81

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:42.610856+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:18:28.471852+00:00, confidence not recorded.
  - readme: https://github.com/handy-computer/transcribe.cpp (fetched 2026-08-28T04:05:42.610856+00:00, sha 796a70951b1b)
  - homepage: https://huggingface.co/handy-computer (fetched 2026-08-29T10:57:36.812475+00:00, sha 5695d5b834e3)
  - site_page: https://huggingface.co/docs (fetched 2026-08-29T10:57:36.815019+00:00, sha bdec26667b98)
  - site_page: https://huggingface.co/docs/hub/organizations-cards (fetched 2026-08-29T10:57:36.818882+00:00, sha 635040b5f704)
  - site_page: https://huggingface.co/pricing (fetched 2026-08-29T10:57:36.816861+00:00, sha de6b7a178be5)
  - site_page: https://huggingface.co/handy-computer/multitalker-parakeet-streaming-0.6b-v1-gguf (fetched 2026-08-29T10:57:36.820519+00:00, sha fad9f89cf81a)
  - site_page: https://huggingface.co/huggingface (fetched 2026-08-29T10:57:36.822670+00:00, sha a64a0fe552e5)
- Data as of 2026-08-30T08:39:29.467469+00:00.