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Whisper as a desktop tool — without Python, without a cloud account.

When you want to use OpenAI Whisper on your own machine but do not want to glue together a Python environment, manage CUDA wheels, or pay for a cloud account, WhisPaste ships whisper.cpp inside a native desktop app — one installer, one hotkey, and the transcript lands at your cursor.

Setup: one installer, no Python environment

WhisPaste embeds whisper.cpp — the C++ port of OpenAI Whisper — directly inside the desktop binary. After install, you pick a model size from a drop-down, the app downloads it once, and from then on transcription runs fully offline on your machine. No virtualenv, no pip, no CUDA toolkit; the GPU acceleration is bundled via Vulkan or CUDA runtimes where available.

Performance: CPU works, GPU is five times faster

whisper.cpp runs on plain CPU on every supported machine (Windows 10+, macOS 10.15+), so an 8 GB laptop without a discrete GPU is enough for the compact model. On a machine with a dedicated GPU — NVIDIA CUDA, AMD or Intel Vulkan — the same transcript is produced roughly five times faster. Apple Silicon uses unified memory, so 8 GB already covers the balanced model.

Local vs cloud: same Whisper, different trade-offs

Local Whisper keeps audio on your machine, costs nothing per minute, and works without internet — at the price of a one-time model download and slightly more RAM. Cloud providers like OpenAI, Groq, or Deepgram trade those resources for raw speed and the largest models. WhisPaste lets you pick per session: stay local by default, switch to a cloud provider when you need maximum speed on a long recording.

  1. Install WhisPaste and pick a Whisper model

    Download WhisPaste from the Microsoft Store, the Mac App Store, or GitHub. On first launch the setup assistant suggests a model size based on your hardware — compact for an 8 GB laptop, balanced for 16 GB with a GPU, premium for higher VRAM.

  2. Let the model download once

    WhisPaste fetches the chosen whisper.cpp model file in the background and verifies it. The download resumes after interrupted connections, so a flaky network does not force you to start over. After that, transcription runs fully offline.

  3. Press your hotkey and speak

    Place the cursor wherever you want the text, hold your configured hotkey, and speak. whisper.cpp transcribes the audio on your machine and the transcript appears at the cursor — no upload, no browser tab, no copy-paste step.