The author of the Handy project announced the release of transcribe.cpp, a C++ transcription library built on the ggml framework. The release comes as developers seek a single, reliable implementation for speech‑to‑text tasks that can run locally on a variety of platforms. Existing options such as whisper.cpp and ONNX require separate model adaptations for different engines, and CPU‑only inference often falls short of performance targets. transcribe.cpp supports 16 ASR families and more than 60 models, with acceleration options for Vulkan, Metal, CUDA and TinyBLAS. The author reports that the library has been numerically validated against reference implementations and that word‑error‑rate tests confirm equivalence with the original models. It provides streaming and batch transcription capabilities and can run on CPUs, GPUs or specialized hardware such as the RK3566. The library is presented as a drop‑in replacement for whisper.cpp, allowing use of existing model files while adding support for GPU‑accelerated inference. It includes bindings for Python, JavaScript/TypeScript, Rust and Objective‑C/Swift, and the author invites community contributions for additional language interfaces. The author notes that local inference reduces reliance on cloud services and can operate in low‑power environments, citing an RK3566 device that processes models faster than real time with minimal wattage. While the library currently covers most publicly available models, the author plans to add missing models and expand language bindings. The project will be maintained as part of the Handy ecosystem. The author thanked Mozilla AI, ggml contributors, Modal, Blacksmith and Hugging Face for support and resources that facilitated testing, CI/CD and model distribution. The release represents a step toward making high‑quality speech transcription more accessible on consumer devices, though broader adoption will depend on further development and community participation.