Turn long videos into captioned shorts on your desktop.

Download for Windows, macOS or Linux  ·  website  ·  faq

Turn podcasts, webinars, streams and interviews into ready-to-post vertical clips.
AI-picked moments, virality scores, animated captions, auto zoom and speaker-aware reframing.

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Download and get started

1. Download the latest release. Choose the Windows .exe installer, macOS .dmg, or Linux .AppImage under Assets. You do not need Node.js or a source checkout to use the app.
2. Set up your connection. In v0.10.0 and newer, the first-run wizard offers ChatGPT sign-in via Codex for AI clip finding with local transcription, an OpenAI-compatible API for separately billed analysis, or Local captions only to caption a whole video without an AI connection. Setup requirements and choices are explained step by step. You can also explore the editor before setting up a connection.
3. Import a video or paste a supported URL. Choose Find viral clips to review suggested moments, or Caption whole video to make one captioned edit. Adjust the trim, captions and framing, then export an MP4.

The ChatGPT/Codex option is a beta integration with your plan's Codex allowance, not an included OpenAI API. It needs the Codex CLI signed in with ChatGPT and Python 3.10+; the wizard can install local faster-whisper and a speech model after you choose it. AI clip finding still needs either Codex or an API connection. Builds before v0.10.0 do not show the wizard; configure the connection in Settings → General → AI connection instead.

The macOS download supports Apple Silicon (M1 or newer). It is currently unsigned and not notarized, so macOS may require System Settings → Privacy & Security → Open Anyway after the first launch attempt. Intel Macs do not currently have a published installer. Platform-specific install notes cover the available builds.

Why Cutawan instead of Opus Clip?

Opus Clip is great, but it costs a subscription, runs in the cloud, and uploads your footage. Cutawan is a free desktop app: connect an OpenAI-compatible API, use ChatGPT sign-in through Codex with local Whisper, or caption whole videos entirely locally.

	Cutawan	Opus Clip (and similar SaaS)
Price	Free and open source (MIT). Bring an API key or eligible ChatGPT/Codex access	Monthly subscription
Your footage	Stays on your machine. Speech can run locally; analysis sends transcripts and sampled frames to your chosen connection	Uploaded to their cloud
Processing minutes	Unlimited	Capped per plan
Watermark	Your own logo, or none	Removed on paid tiers
Models	Your choice (GPT-5 series, or the budget legacy option)	Theirs
Extensible	Fork it, script it, PR it	Closed

On the default API route, a typical estimate is ~$0.36/hour of video for Whisper transcription plus a few cents of LLM analysis with gpt-5.4-mini; actual API charges depend on usage and current pricing. The ChatGPT/Codex route uses plan allowance and local speech transcription instead.

What it looks like

Pick how you want to work on first launch. Local captions do not need an AI connection.

Pick a mode at setup: let the AI find clips, or caption the whole video end to end.

Features

Two ways to work

• Find viral clips. The AI reads the transcript, cuts the best moments out and scores them, and you pick from the results.
• Caption the whole video. No clip finding: give it a 16:9 video and it comes back as one vertical, captioned edit you can trim, restyle and export. Optionally tracks the speaker across the whole video and adds auto zoom. Both modes work on the same project, and the transcript is shared between them.

Finding the clips

• Import anything. Local files (MP4/MOV/MKV/WEBM and more) or paste a URL from YouTube, Vimeo, TikTok, Twitch, or any site yt-dlp supports. Private or SSO-protected videos (like enterprise Vimeo) work by borrowing the login from your browser. No server integration needed.
• Whisper transcription with word-level timestamps. Long videos are chunked automatically and checkpointed, so retries and re-generations never pay for transcription twice.
• Viral moment detection backed by research. An LLM picks self-contained hook, build, payoff micro-stories (not clips that trail off mid-setup). You can steer it with your own prompt if you want, like "find the funniest exchanges". A second AI pass reviews every clip ending and extends it to the beat that actually completes the thought.
• Two-pass virality scoring (0-99). A text rubric based on Berger and Milkman's What Makes Online Content Viral? (JMR 2012), plus measured vocal energy, combined with a vision pass from Kayal et al. (ACL 2025) that scores sampled frames for scroll-stopping potential.

Making them good

• Auto zoom. Scene-aware punch-ins on the speaker's most energetic lines, jump zooms that cover cuts, and slow creep on static stretches. The kind of thing top short-form editors do to keep people watching.
• Tighten cuts. Pauses and filler words ("um", "uh") get removed automatically. Captions, B-roll, zoom and the face track all remap to the shorter timeline.
• Speaker-aware auto-reframe. On-device audio-visual active speaker detection (UltraFace face tracking + the LR-ASD model via ONNX Runtime, no cloud) checks every face's lip movement against the actual soundtrack, so the crop stays on the person talking — not whoever moves or gestures. The 9:16 crop cuts between speakers like a camera switch.
• 12 caption styles plus your own fonts. Karaoke-style word highlighting burned in with libass. Upload any TTF/OTF and previews match exports exactly.
• Your branding. Overlay your logo or watermark (corner, size, opacity) on the preview and every export.
• AI B-roll. Say "Yoda" and a picture of Yoda pops over the video at that word. Uses Wikipedia and Openverse images, no extra API keys.
• A real editor. Filmstrip trim with waveform and live playhead, click-to-seek transcript that doubles as a trim tool, aspect ratios (9:16 / 1:1 / 16:9), and a live preview that matches the export.

Shipping them

• Export H.264/AAC MP4s with burned-in captions. Loudness-normalised to -14 LUFS, gentle audio tail fade, three quality tiers, NVIDIA NVENC GPU encoding with automatic CPU fallback. Optionally encode once to fit under a megabyte cap (Discord, email, WhatsApp).
• AI post captions. One click writes a scroll-stopping TikTok/Reels/Shorts caption (hook-first line, one engagement driver, niche hashtags). Copy it and jump straight to TikTok Studio upload.
• Update notifications. Windows/Linux packages download and install updates in the app. Unsigned Mac builds download and verify the installer in the app, then guide you through replacing it in Applications. Source checkouts update with one click (pull, rebuild, relaunch).

Website

The marketing website is cutawan.xyz. Its source lives in the separate private cutawan-website repository. App releases and documentation remain here.

Build from source

For contributors and developers; everyone else can use the prebuilt downloads.

git clone https://github.com/JeremySNR/cutawan.git
cd cutawan
npm install
npm run dev        # development with hot reload
npm run package    # distributable build (dmg / nsis / AppImage)

Publishing a release (for maintainers)

Most people should just download the app from the releases page — there's no need to run anything from source. To cut a new release, bump the version and push a tag; the Release workflow builds the macOS .dmg, Windows installer and Linux AppImage and publishes them, along with the update manifests the in-app updater reads:

npm version patch        # or minor / major — bumps package.json and creates the tag
git push --follow-tags   # pushes the commit and the vX.Y.Z tag

Windows packages can also be listed on winget after a one-off first submit.

Windows/Linux packages support in-app installation of later releases. The macOS app is not Developer ID signed or notarized, so it downloads and verifies a Mac installer, then offers Open installer. Quit Cutawan and replace the app in Applications; projects and settings remain in the app-data folder. Proper Mac signing/notarization requires Apple Developer Program membership. Before enabling Mac auto-updates, wire the signing credentials into the workflow and verify an upgrade between two signed releases.

Updates are checked on launch and every six hours, with retries after a failed check or reconnection. The toolbar shows download progress and readiness, and opens Settings → Updates directly. Windows/Linux installation requires an explicit restart and is blocked while work is active. The release workflow verifies every platform’s installer and manifest before publishing a completed draft.

The Mac release is built for Apple Silicon. CI and the release workflow run bash scripts/check-mac-package.sh against the packaged app before publication. This checks native binary architecture, isolated inference, speaker-model batch parity, saved projects, captioned export, first-run setup, and the assisted-update UI (available, downloading, retry, and ready states). Run GUI checks from a normal macOS GUI session; an agent's restricted shell can fail in Launch Services before Electron starts. Native ONNX processing runs in a child process with bounded frontend batches so a native failure cannot terminate the editor.

Building from source needs Node.js 20+. The local speech routes need Python 3.10+; the wizard can install faster-whisper and a speech model into Cutawan's app-data folder. FFmpeg is bundled. On Windows, winget install JeremySNR.Cutawan will work once the winget package is listed.

Rendering, face tracking, editing, zoom and export run locally. Speech can also run locally with faster-whisper. For API transcription, extracted audio goes to the configured endpoint; analysis sends transcript text and sampled frames through the selected connection. The full video is never uploaded.

Architecture

src/
├── main/                  Electron main process
│   ├── pipeline/
│   │   ├── ffmpeg.ts      probe, audio chunk extraction, thumbnails
│   │   ├── openai.ts      minimal REST client (Whisper + structured chat)
│   │   ├── transcribe.ts  chunked transcription, timestamp stitching
│   │   ├── highlights.ts  LLM viral-moment detection, scoring, ending review
│   │   ├── faces.ts       auto-reframe orchestration + focus track building
│   │   ├── asd.ts         LR-ASD audio-visual active speaker detection
│   │   ├── facetracks.ts  per-person face tracking (IOU + interpolation)
│   │   ├── detect.ts      UltraFace face detection + scene-cut detection
│   │   ├── mfcc.ts        MFCC audio features for the ASD model
│   │   ├── energy.ts      per-segment vocal energy (arousal signal)
│   │   ├── ytdlp.ts       yt-dlp binary management + URL downloads
│   │   ├── broll.ts       LLM keyword tagging for B-roll inserts
│   │   ├── imagesearch.ts keyless Wikipedia/Openverse image search
│   │   ├── encoders.ts    NVENC detection/verification, GPU ffmpeg download
│   │   ├── captions.ts    ASS karaoke subtitle generation
│   │   ├── socialCaption.ts AI post-caption writer
│   │   └── render.ts      cut, reframe, auto zoom, watermark, burn-in
│   ├── updates.ts         GitHub release checks + self-update
│   ├── fonts.ts           custom caption fonts (sfnt parsing, merged fontsdir)
│   ├── ipc.ts             typed IPC handlers
│   ├── settings.ts        encrypted API key, models, branding
│   └── projects.ts        project persistence (userData/projects)
├── preload/               context-isolated typed bridge
├── shared/                types, caption styles/layout, tighten + zoom planners
└── renderer/              React UI (Tailwind, Zustand)

The live preview and the export share the same planning code in src/shared/ (caption layout, tighten cuts, zoom), so what you see is what gets rendered.

Tests

Unit tests, typecheck and lint run in CI on every push, alongside the offline pipeline test and a UI smoke test:

npm test               # vitest unit tests
npm run typecheck
npm run lint

Integration test scripts live in scripts/ (test-pipeline, test-e2e, test-quality, test-wholevideo, test-encoders, test-resilience, test-broll, test-youtube, test-asd, smoke-test.sh). See each file's header for what it covers. The e2e ones need OPENAI_API_KEY.

To measure clip quality on your own projects, scripts/eval-clips.ts reads every saved project and reports how many clips open mid-sentence, cut a sentence off, or trail into dead air, plus the length spread. Add --rerun (needs OPENAI_API_KEY, a few cents per project, no transcription cost) to re-run clip detection on the saved transcripts with the current prompts and compare, which is how to check a prompt change actually helps:

npx tsx --tsconfig tsconfig.node.json scripts/eval-clips.ts --verbose

The bundled active-speaker model (resources/models/lr-asd-*.onnx) is exported from the MIT-licensed LR-ASD weights with scripts/export-asd-onnx.py (requires Python with torch, onnx, onnxruntime, python_speech_features).

FAQ

Is it actually free? The app is free and MIT licensed. The API route incurs separate provider charges; the ChatGPT/Codex route uses your existing plan allowance and local Whisper. Neither route adds a Cutawan subscription or paid feature tier. Provider limits and charges still apply.

Do I need an OpenAI API key? No. The first-run wizard also offers ChatGPT sign-in via Codex for analysis, paired with local Whisper transcription, and a local-only route for whole-video captions (without AI clip finding). ChatGPT's subscription is separate from OpenAI API billing, and Codex plan limits apply. Everything else runs locally without an API key: the editor, trimming, caption styling, auto zoom, speaker reframing, watermarks and export. If you already have a transcript from a previous run, you can keep editing and exporting offline.

Does my video get uploaded anywhere? The full video is not uploaded. On the API route, extracted audio, transcript text and sampled frames are sent to the configured endpoint. On the ChatGPT/Codex route, speech is transcribed locally and only transcript text and sampled frames are sent for analysis. Rendering, face tracking, zoom and export are local.

Can I use my Claude subscription? Not as Cutawan's AI connection. Anthropic's guidance directs developers of third-party apps, including open-source apps, to use API-key authentication. Cutawan will not route automated requests through a personal Claude login.

How is this different from Opus Clip's free tier? Free SaaS tiers cap your processing minutes and usually watermark the output. Cutawan has no cap because it runs on your hardware, and the only watermark is one you add yourself.

Do I need a GPU? No. Cutawan uses NVIDIA NVENC if it finds it and falls back to CPU encoding automatically. A GPU makes exports faster, nothing more. Speaker detection runs on-device through ONNX Runtime and is fine on CPU.

How long can my video be? There is no fixed limit. Audio is chunked and transcription is checkpointed to disk as it goes, so hour-plus recordings work and a failure part way through does not mean paying to transcribe it again.

Does it work in languages other than English? Transcription does. Set the language in Settings (it defaults to English, which is more reliable than auto-detect, since auto occasionally mislabels English as something else). Captions burn in whatever Whisper returns. Translating captions into another language is on the roadmap, not built yet.

Can it post to TikTok or YouTube for me? Not automatically. It writes the post caption and hands you the file, then you upload. Direct publishing needs an audited TikTok/YouTube app, which is on the roadmap and a good contribution if you fancy it.

Can I use the clips commercially? Yes. MIT licence, and the output is yours. Do check the rights on any source footage you did not create, and note that AI B-roll pulls from Wikipedia and Openverse, whose images carry their own licences.

macOS says the app cannot be opened. Why? The macOS builds are not code-signed yet, so Gatekeeper may block first launch. After trying to open the app, use System Settings → Privacy & Security → Open Anyway. Signing and notarisation are wanted; see CONTRIBUTING.md if you can help.

Which OpenAI models does it use? whisper-1 for transcription and gpt-5.4-mini for analysis by default. Both are configurable in Settings, including a cheaper legacy option.

Can I run it against a local or non-OpenAI model? Yes, if it speaks the OpenAI REST shape. Set the API base URL in Settings (or OPENAI_BASE_URL) to Azure OpenAI, OpenRouter, Groq, LM Studio, Ollama, or anything else with /v1/chat/completions. Transcription can point at a separate local Whisper server (faster-whisper, whisper.cpp’s compatible endpoint) — it must return word-level timestamps, because captions and tighten-cuts depend on them. The ChatGPT/Codex route instead uses local faster-whisper directly, with an in-app installer and no server.

Roadmap

Each of these is an open issue, so the discussion and the detail live there. Contributions very welcome.

• Multi-language caption translation
• Manual zoom keyframes on the timeline
• Easier fully bundled on-device Whisper, without requiring a separate Python installation
• Direct publishing and scheduling to socials (needs an audited TikTok/YouTube app)

Looking for somewhere to start? The good first issues need no deep knowledge of the pipeline.

Contributing

Issues and PRs are welcome. The codebase is TypeScript end-to-end. npm test && npm run typecheck && npm run lint must pass. CI enforces all three plus an offline render test.

See CONTRIBUTING.md for setup (including how to explore the UI without an API key), how the code is laid out, and the handful of things that are easy to get wrong. Release history is in CHANGELOG.md. Security issues go through SECURITY.md rather than a public issue.

License

MIT

On Windows cmd.exe (and PowerShell), don't paste the # comments in the examples above — they aren't comment characters there and get passed to the script as arguments. Run just npm run dev.

Troubleshooting: Error: Electron uninstall

If npm run dev fails with Error: Electron uninstall (or An entry point is required… right before it), the Electron runtime binary didn't finish downloading during npm install — a common consequence of a dropped/interrupted connection. node_modules/electron/dist/ ends up missing electron.exe. Fix it without a full reinstall:

npm rebuild electron

If that no-ops and the binary is still missing, force a clean re-download:

# macOS / Linux
rm -rf node_modules/electron/dist node_modules/electron/path.txt
force_no_cache=true node node_modules/electron/install.js

# Windows PowerShell
Remove-Item -Recurse -Force node_modules\electron\dist, node_modules\electron\path.txt -ErrorAction SilentlyContinue
$env:force_no_cache = "true"; node node_modules/electron/install.js

Verify with npx electron --version (should print the Electron version, e.g. v35.7.5). Note that npm run package can succeed even while this is broken — electron-builder downloads its own copy of Electron separately from the dev runtime.

Screenshots and brand assets

Run npm run screenshots to build Cutawan and capture the first-run wizard plus eight app views with isolated offline demo profiles. See rename notes for existing-install compatibility and screenshot details.