Transcribe any audio using Whisper AI — runs entirely in your browser. Private, free, no sign-up, no upload to servers.
Whisper is the standard for high-quality open-source transcription. Historically that meant Python, a GPU, and a command-line workflow — completely inaccessible to most people. Running Whisper in the browser flips that: drop an audio file, transcribe it, download SRT or TXT. No installs, no accounts, no code.
The privacy story is decisive for sensitive audio. Client-side Whisper means the audio never leaves your device. Interview recordings, medical dictation, legal depositions, confidential meetings — anything you can't ethically or legally upload to a third-party API — is now transcribable without risk.
Common workflows: journalists cleaning up interview audio, podcasters generating episode transcripts for SEO, YouTubers creating SRT files for their videos, students transcribing lectures, researchers processing recorded conversations.
Whisper comes in several sizes. Smaller = faster but less accurate. Larger = slower but more accurate. In the browser, the trade-off matters more because you're limited by device compute.
tiny / base: fastest, adequate for clean audio in major languages. Good for a first pass or when speed matters more than perfect transcription.
small / medium: the practical sweet spot for most users. Handles accents, background noise, technical vocabulary reasonably well. Reasonable speed on modern devices.
large: highest accuracy but heavy — expect 30 seconds of compute per minute of audio on typical hardware. Use for critical transcripts you'll publish.
Set language explicitly if you know it — auto-detect adds latency and can misfire on short clips.
Clean audio matters more than model size. A tiny model on a clean recording beats a large model on muddy audio. If you have control over the recording, use a decent microphone, minimize background noise, and record close-mic.
For SRT subtitles, the segmentation Whisper produces is usable but rarely perfect for reading. Consider running a light post-edit — split long lines, adjust punctuation — before shipping to YouTube.
Very long files (2+ hours) may hit browser memory limits. Split into 30-minute chunks with any audio editor, transcribe each, then concatenate.
Yes — the model weights are identical. The only difference is compute speed, which depends on your device rather than the model quality.
MP3, WAV, M4A, MP4, WebM, OGG, FLAC — anything the browser can decode via the Web Audio API. Video files are supported too; the audio track is extracted.
Yes — after the model downloads once (cached in the browser), transcription runs fully offline. Great for airplane workflows or air-gapped devices.
Whisper supports 99 languages. Leave language on Auto-detect for best results on unknown audio, or set explicitly if you know the language for slightly faster/more accurate results.
No. Audio is decoded and transcribed entirely inside your browser using WebAssembly. Nothing is uploaded, stored, or logged.
Whisper is compute-heavy. On older laptops or phones, the large model can be very slow. Switch to a smaller model, or use our Groq Whisper tool (uses cloud compute with a free API key) for near-instant results on large files.