whisper.cpp is an open-source implementation of OpenAI's Whisper speech recognition models, converted for efficient local and server-side inference. Below are 12 voice, tts & speech apps with similar functionality to Whisper.cpp, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
whisper-large-v3-turbo is an open-source automatic speech recognition model for transcribing audio to text. It is available for local inference via CLI and is intended for AI researchers and developers.
whisper-medium-gguf is an open-source automatic speech recognition model based on OpenAI's Whisper, supporting transcription and translation in 99 languages. It is compatible with transcribe.cpp and enables local, multilingual speech-to-text applications.
Whisper is a web application that enables users to transcribe or translate spoken audio into written text. Users can upload audio files, record directly, or provide YouTube links, and receive accurate transcriptions or translations. It is ideal for content creators, journalists, and researchers.
whisper-large-v3-turbo is an open-source automatic speech recognition (ASR) model designed for transcribing audio into text. It supports multiple languages and offers fast, accurate transcription for developers and researchers working on speech processing applications. The model is distributed under an open license for local deployment.
whisper-local is a free, open-source AI dictation tool for Windows and macOS that transcribes speech to text entirely offline using Whisper models. It offers hotkey activation and privacy-focused local processing for users needing secure voice typing.
whisper-large-v3-turbo-mlx-8bit is an open-source speech recognition model based on Whisper, quantized for efficient on-device inference using MLX. It enables developers to perform speech-to-text transcription locally, making it suitable for privacy-focused or offline applications.
oreero-whisper-sk is an open-source Slovak speech recognition model package for WhisperKit and Core ML. It enables offline, on-device transcription of Slovak audio, supporting developers and researchers working on speech-to-text applications in the Slovak language.
Whisper Webui is a web-based application that enables users to transcribe audio files into text using AI models. It supports multiple languages and provides downloadable transcriptions, ideal for journalists and researchers.
whisper-large-v3-onnx is an open-source ONNX-converted version of the Whisper large v3 model for automatic speech recognition. It enables developers to run speech-to-text inference locally or integrate with JavaScript environments using transformers.js. Suitable for building custom ASR solutions.
hwdsl2/whisper-server is a self-hosted speech-to-text server that provides an OpenAI-compatible API for audio transcription and translation. It is designed for users seeking a private, on-premise solution for converting audio files into text, with a focus on simplicity and security. The server operates as a Docker image and is powered by faster-whisper, enabling deployment on a variety of Linux systems, including those with amd64 and arm64 architectures. The tool supports all Whisper models, including tiny, base, small, medium, large-v3, and large-v3-turbo, allowing users to choose the model that best fits their requirements. It offers speaker diarization as an optional local extension using sherpa-onnx, which enables identification of individual speakers in audio segments. Model management is facilitated through a helper script, whisper_manage, and a persistent model cache is maintained via a Docker volume. Audio files remain on the user's server, ensuring that no data is sent to third parties. The server accepts all major audio formats, such as mp3, m4a, wav, webm, ogg, flac, and any format supported by ffmpeg. The API exposes endpoints compatible with OpenAI's POST /v1/audio/transcriptions and POST /v1/audio/translations, enabling seamless integration with existing applications that use the OpenAI Whisper API. Multiple response formats are available, including JSON, plain text, verbose JSON, SRT subtitles, and WebVTT subtitles. The platform also supports streaming transcription, where segments can be received via server-sent events as they are decoded. For users with NVIDIA GPUs, a CUDA-accelerated image is available, offering faster inference on supported hardware. The system can operate in offline or air-gapped mode using pre-cached models, and is suitable for both local and cloud deployments. 12-slim) and is part of a broader self-hosted AI stack. It is automatically built and published via GitHub Actions. The tool is intended for developers, organizations, and anyone needing private, self-hosted audio transcription and translation capabilities with OpenAI API compatibility.
Whisper Large V2 is a web application that transcribes audio files into text using a large-scale speech recognition model. Users can upload audio and receive accurate transcriptions, making it useful for transcription tasks and accessibility.
Whisper To Stable Diffusion is a web application that transcribes spoken prompts using speech-to-text AI and then generates images from the transcribed text using image generation models. It is designed for AI enthusiasts and creators who want to explore multimodal AI workflows.
