whisper.cpp vs meetily
Two of the top projects in Voice, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
whisper.cpp
C/C++ port of OpenAI Whisper for local speech-to-text transcription
meetily
Desktop app that records, transcribes and summarizes meetings locally
Verdict
whisper.cpp ranks higher, 74 to 64. Of the 5 score parts we measure for both, whisper.cpp leads on 2, meetily on 1 and 2 are even.
- Adoptionwhisper.cpp leads by 19 points, 74 to 55: a wide gap.
- FreshnessEven at 100.
- Maintenancewhisper.cpp leads by 33 points, 97 to 64: a wide gap.
- Easy to runEven at 50.
- Agent-readymeetily leads by 10 points, 40 to 30.
Pick whisper.cpp if you are
Developers embedding offline speech-to-text in apps, servers or devices
- No dependencies in core; zero memory allocations at runtime
- Wide backend coverage: Metal, Core ML, CUDA, Vulkan, ROCm, OpenVINO, CANN, MUSA, NPU
Pick meetily if you are
Professionals who want private, local meeting transcription and notes
- Transcription runs on-device with Whisper or Parakeet; no cloud needed
- Summary provider is selectable, including local Ollama or a custom OpenAI-compatible endpoint
| What we compare | whisper.cpp | meetily |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 74, popular | 55, popular |
| Freshness | 100, active | 100, active |
| Maintenance | 97, healthy | 64, fair |
| Easy to run | 50, easy | 50, easy |
| Agent-ready | 30, minimal | 40, minimal |
| Facts from GitHub and the README | ||
| Stars | 54.4k | 31.7k |
| License | MIT (permissive) | MIT (permissive) |
| Last commit | Oct 2026 | Sep 2026 |
| Last release | Oct 2026 | Sep 2026 |
| Language | C++ | Rust |
| Docker | Yes | No |
| GPU | Optional | Optional |
| arm64 or Apple Silicon | Mentioned | Mentioned |
whisper.cpp
whisper.cpp runs OpenAI's Whisper speech recognition models in plain C/C++ on top of the ggml library, with a C-style API in whisper.h and a whisper-cli example for transcribing 16-bit WAV files. It runs on CPU or can offload to Metal, Core ML, CUDA, Vulkan, ROCm, OpenVINO, Ascend CANN, Moore Threads MUSA and AMD Ryzen AI NPUs. It supports integer quantization and voice activity detection, and builds for desktop, mobile, WebAssembly and Docker.
Who it is for: Developers embedding offline speech-to-text in apps, servers or devices
Strengths
- No dependencies in core; zero memory allocations at runtime
- Wide backend coverage: Metal, Core ML, CUDA, Vulkan, ROCm, OpenVINO, CANN, MUSA, NPU
- Runs on iOS, Android, WebAssembly, Raspberry Pi, and Java bindings exist
- Q5_0-style integer quantization shrinks models; base model needs about 388 MB RAM
Weaknesses
- whisper-cli accepts only 16-bit WAV unless built with optional FFmpeg support
- Core ML, OpenVINO and VitisAI encoders need a separate Python conversion step
- Models must be in ggml format; downloaded via script, not bundled
- Library and CLI only; no built-in web UI or multi-user features
- GPU optional
- Docker
- Needs CMake, ffmpeg (optional), CUDA / ROCm / Vulkan / OpenVINO (optional backends)
- Models: Whisper ggml (tiny, base, small, medium, large-v1/v2/v3, large-v3-turbo), Quantized ggml (e.g. q5_0)
meetily
Meetily is a Tauri desktop app with a Rust backend and a Next.js frontend. It captures microphone and system audio, transcribes on-device with Whisper or Parakeet models, and generates summaries through Ollama, Claude, Groq, OpenRouter, or any OpenAI-compatible endpoint. Installers exist for Windows and macOS; Linux requires a source build.
Who it is for: Professionals who want private, local meeting transcription and notes
Strengths
- Transcription runs on-device with Whisper or Parakeet; no cloud needed
- Summary provider is selectable, including local Ollama or a custom OpenAI-compatible endpoint
- Records microphone and system audio together with mixing
- Imports existing audio files and re-transcribes with another model or language (beta)
Weaknesses
- No prebuilt Linux package; must build from source
- Speaker diarization is not in the community edition; planned for PRO
- Custom summary templates, advanced exports and auto-join are PRO-only
- Standard Windows installer uses Vulkan; CUDA needs a source build
- GPU optional
- Needs Ollama (optional, for local summaries)
- Models: Whisper, Parakeet (ONNX), Ollama, Claude, Groq
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