Meetily vs whisper.cpp
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
Free, open-source meeting notes app for macOS and Windows that transcribes and summarizes locally.
Open source · MIT
Fast C/C++ port of OpenAI's Whisper speech-to-text model, runs locally on CPU or GPU.
The short answer
Choose Meetily if you need…
- People who want meeting notes without sending recordings to a cloud service
- Professionals handling sensitive conversations who need control over where data is stored
- Users on macOS or Windows who want a free, MIT-licensed alternative to paid note takers
- Teams with their own OpenAI-compatible AI infrastructure who want to point summaries at it
Choose whisper.cpp if you need…
- Developers who want to embed offline speech-to-text in a C, C++, or other native app
- People on Apple Silicon who want GPU or Neural Engine accelerated transcription
- Users who need to transcribe audio privately on their own computer
- Projects targeting constrained or embedded hardware such as Raspberry Pi
Side-by-side
| Meetily | whisper.cpp | |
|---|---|---|
| Type | App | Library |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 32.4k | 54.9k |
| Setup difficulty | Beginner | Intermediate |
| How you get it | Download the app | Clone and build from source |
| Main language | Rust | C++ |
| Last code update | 5 days ago | 7 days ago |
What each one is
Meetily
Meetily is a desktop app that records your meetings, turns the audio into a live transcript, and can generate summaries. The README says transcription runs on your own device using Whisper or Parakeet models, so audio and transcripts are meant to stay local. Summaries can use a local model through Ollama or a cloud provider you choose, such as Claude, Groq, OpenRouter, or an OpenAI-compatible endpoint.
whisper.cpp
whisper.cpp is a C/C++ implementation of OpenAI's Whisper automatic speech recognition model, which turns spoken audio into text. It is written to run with no external dependencies and can work offline on the device. People use it to add transcription to their own apps or to transcribe audio on their own machine without sending it to a cloud service.
Best for
Meetily
- People who want meeting notes without sending recordings to a cloud service
- Professionals handling sensitive conversations who need control over where data is stored
- Users on macOS or Windows who want a free, MIT-licensed alternative to paid note takers
- Teams with their own OpenAI-compatible AI infrastructure who want to point summaries at it
whisper.cpp
- Developers who want to embed offline speech-to-text in a C, C++, or other native app
- People on Apple Silicon who want GPU or Neural Engine accelerated transcription
- Users who need to transcribe audio privately on their own computer
- Projects targeting constrained or embedded hardware such as Raspberry Pi
Strengths
Meetily
- Transcription is designed to run on the local device, which the README describes as a core privacy feature
- Free and open source under the MIT license
- Supports multiple AI providers, including fully local ones through Ollama
whisper.cpp
- No external dependencies in the core implementation, which eases integration into many platforms
- Supports a wide range of hardware including CPU, Metal, CUDA-based NVIDIA GPUs, Vulkan, and Core ML
- Includes quantization options that reduce model size and memory use
Not ideal for
Meetily
- Linux users who want a packaged installer, since the README says Linux requires building from source
- People who need cloud-only convenience and do not want to manage local models or providers
- Users who need speaker diarization now, since the README says it is planned for the paid PRO edition and the free build's status is not clearly stated
whisper.cpp
- Non-technical users who want a ready-made app with a graphical interface, since the README centers on command-line usage and building from source
- Anyone who needs audio in formats other than 16-bit WAV without first converting it, because the CLI example only accepts 16-bit WAV
- Teams needing a hosted transcription API, since this is a local inference library rather than a service
Trade-offs
Meetily
- Linux requires building from source, which takes more technical effort
- The README mentions GPU acceleration differs by platform and build, so performance depends on your hardware; Windows needs an AVX2-capable x64 CPU
- Some features, such as speaker diarization and advanced exports, are mentioned as PRO or planned items, so the free edition may not include everything the marketing copy describes
whisper.cpp
- Command-line example only accepts 16-bit WAV, so audio often needs conversion first
- Building and choosing models requires comfort with CMake and the terminal
- Core ML and some accelerator paths require extra setup and platform-specific steps
Getting started
Meetily
Clone the repository (Linux build from source)
git clone https://github.com/Zackriya-Solutions/meeting-minutesInstall frontend dependencies (Linux build)
pnpm install --frozen-lockfilewhisper.cpp
Clone the repository
git clone https://github.com/ggml-org/whisper.cpp.gitDownload the base.en model
sh ./models/download-ggml-model.sh base.enFrequently asked questions
What is the difference between Meetily and whisper.cpp?
Meetily: Free, open-source meeting notes app for macOS and Windows that transcribes and summarizes locally. whisper.cpp: Fast C/C++ port of OpenAI's Whisper speech-to-text model, runs locally on CPU or GPU. Meetily suits people who want meeting notes without sending recordings to a cloud service, while whisper.cpp suits developers who want to embed offline speech-to-text in a c, c++, or other native app.
Are Meetily and whisper.cpp free?
Meetily: Free and open source. whisper.cpp: Free and open source.
Which is easier to set up, Meetily or whisper.cpp?
Meetily is easier to get started with (rated beginner); whisper.cpp is rated intermediate and usually needs more setup.
Is Meetily or whisper.cpp more popular?
whisper.cpp has more GitHub stars (54.9k) than Meetily (32.4k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to Meetily and whisper.cpp?
Other options people compare them with include omi, OpenWhispr, Voicebox, faster-whisper, Whisper.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.