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whisper.cpp vs Buzz

whisper.cppBuzz

Fast offline speech-to-text on your own machine.

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Transcribe and caption audio offline on your computer.

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Votes00
PricingFreeFree
CategoryTranscriptionTranscription
Tags
practical-ossopen-sourceself-hostedtranscription
practical-ossopen-sourceself-hostedtranscription
Best for——
Pros
  • Runs entirely offline and locally, so audio never leaves your device
  • Plain C/C++ with no runtime dependencies, making it easy to embed and ship in other apps
  • Broad hardware support including CPU-only, Apple Silicon (Metal/Core ML), NVIDIA CUDA, Vulkan and AMD ROCm
  • Quantization and multiple model sizes let you trade accuracy for speed and memory down to tiny devices
  • MIT licensed with a large ecosystem of language bindings (Python, Go, Rust, Java, Swift and more)
  • Runs fully offline on your own machine, keeping audio private
  • Permissive MIT license
  • Handles files, YouTube links, and live microphone transcription
  • Exports to TXT, SRT, and VTT, with speaker identification and a watch-folder option
  • Hardware acceleration via CUDA, Apple Silicon, and Vulkan for faster processing
Cons
  • It is a developer library/CLI, not an end-user app, so you build or integrate it yourself
  • The CLI expects 16 kHz WAV input, so you often need ffmpeg to convert audio first
  • Features like speaker diarization and word-level timestamps are marked experimental
  • Getting GPU/NPU acceleration working requires building from source with the right flags and toolchains
  • Accuracy and speed depend on the Whisper model size and your hardware; larger models need a capable GPU
  • Whisper's translation feature outputs English, so it is not a general any-to-any translator
  • Installers are unsigned, so Windows and macOS show security warnings on first run
  • Intel Macs are no longer supported beyond an older release; current versions require Apple Silicon

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