Clips.
Clip selection that turns a long recording into ranked shorts and highlights from a transcript. On-device on iPhone or Mac.
Create short videos and highlight clips.
From a 25-minute recording, Clips ranks 12 clips in 9s on an iPhone 17 Pro. Create a ranked selection of clips to share instantly.
Clips analyzes a transcript to find the best moments and stories, and returns a ranked list of clips. Use the ranked selection to create highlight reels or a summary video. Build your own clipping engine or auto-edit, with no inference cost.
Nothing is uploaded, so clipping a back catalog costs the same as clipping one video. There's no length limit or maximum context size. Use Clips on short videos or audio files to get a summary in seconds, or churn through hour-long recordings without limitations.
25 minutes of video, clipped in 9s.
Clips ranks a 25-minute transcript into 12 clips in 9.19s on an iPhone 17 Pro, on the device.
Measured on device, pinned to CPU and Neural Engine
| Transcript | iPhone 17 Pro | iPhone 15 Pro |
|---|---|---|
| 25-minute video, 12 clips | 9.19s | 10.22s |
| Per candidate, encoder only | 2.78ms | 3.13ms |
Internal measurements on the shipped Core ML build. Clip edges are the known weak spot, and selection near a moment is sensitive to small score changes, so a different runtime or quantization returns a different but comparable set.
Shorts from a podcast episode
Post the five best moments of an hour-long episode as shorts, ranked, before the export finishes, in just a few seconds directly on-device.
Auto edit a long take
Turn a rambling 25-minute take into a tight cut in a video editor. Get a highlight reel with the most important insights from a video, ready to review or publish.
Clip the back catalog
Run a library of recorded talks or streams through Clips on a Mac overnight. Nothing is uploaded and nothing is billed per video, so a thousand videos cost the same as one.
Highlights in a hundred languages
A creator app that ships in Spanish, Portuguese, and German gets the same clip selection in all three: one model covers a hundred languages, from the transcript, on the device.
Inspiration
Ideas to build with Clips. Copy a prompt into your coding agent and go.
Turn any recording into a ranked set of shorts.
Build a feature that takes a recording's transcript and uses Desert Ant's Clips to rank the best non-overlapping moments, then exports them as vertical shorts. On-device, so a back catalog costs the same as one video. Build it with the Desert Ant SDK. Clips (Swift). Install and API: https://desertant.com/docs/clips/. Install: SwiftPM desert-ant-core. SDK source: https://github.com/Desert-Ant-Labs/desert-ant-core. Machine-readable catalog of every model and SDK: https://desertant.com/llms.txt.
Generate a highlight reel from a long stream or talk.
Build a 'make highlights' button that runs Desert Ant's Clips over a talk or stream transcript to pick the strongest moments and assemble a highlight reel, ranked best first. Build it with the Desert Ant SDK. Clips (Swift). Install and API: https://desertant.com/docs/clips/. Install: SwiftPM desert-ant-core. SDK source: https://github.com/Desert-Ant-Labs/desert-ant-core. Machine-readable catalog of every model and SDK: https://desertant.com/llms.txt.
Produce a rough auto-edit from a rambling take.
Build an auto-edit that uses Desert Ant's Clips to select the clips worth keeping from a long, rambling recording and lays them on a timeline for review. Control how tight the cut is with the percentile threshold. Build it with the Desert Ant SDK. Clips (Swift). Install and API: https://desertant.com/docs/clips/. Install: SwiftPM desert-ant-core. SDK source: https://github.com/Desert-Ant-Labs/desert-ant-core. Machine-readable catalog of every model and SDK: https://desertant.com/llms.txt.
Clip a whole back catalog of videos overnight on a Mac.
Build a batch job that runs Desert Ant's Clips over an archive of recorded talks or streams on a Mac, exporting ranked clips for each. Nothing uploaded, no per-video bill. Build it with the Desert Ant SDK. Clips (Swift). Install and API: https://desertant.com/docs/clips/. Install: SwiftPM desert-ant-core. SDK source: https://github.com/Desert-Ant-Labs/desert-ant-core. Machine-readable catalog of every model and SDK: https://desertant.com/llms.txt.
Build a full podcast studio: transcribe, clip, and title on the device.
Build a podcast tool that runs Desert Ant's Voz to transcribe an episode, Clips to pick the best moments as shorts, and Title to name and describe each clip, all on-device with no per-minute or per-token bill. Build it with the Desert Ant SDK. Voz (Swift). Install and API: https://desertant.com/docs/voz/. Clips (Swift). Install and API: https://desertant.com/docs/clips/. Title (Swift). Install and API: https://desertant.com/docs/title/. SDK source: https://github.com/Desert-Ant-Labs/desert-ant-core. Machine-readable catalog of every model and SDK: https://desertant.com/llms.txt.
Record, clean, transcribe, and clip: a whole creator pipeline, offline.
Build a creator pipeline: Desert Ant's Clear cleans the recording, Voz transcribes it, and Clips pulls the shorts, all on the device so a full episode never touches a server. Build it with the Desert Ant SDK. Clear (Swift, Kotlin, JavaScript / TypeScript). Install and API: https://desertant.com/docs/clear/. Voz (Swift). Install and API: https://desertant.com/docs/voz/. Clips (Swift). Install and API: https://desertant.com/docs/clips/. SDK source: https://github.com/Desert-Ant-Labs/desert-ant-core. Machine-readable catalog of every model and SDK: https://desertant.com/llms.txt.
Turn a webinar into teaser clips for social.
Transcribe a webinar with Desert Ant's Voz and use Clips to pull the strongest moments as teaser clips for social, on-device. Build it with the Desert Ant SDK. Voz (Swift). Install and API: https://desertant.com/docs/voz/. Clips (Swift). Install and API: https://desertant.com/docs/clips/. SDK source: https://github.com/Desert-Ant-Labs/desert-ant-core. Machine-readable catalog of every model and SDK: https://desertant.com/llms.txt.
Build a fully local clipping engine: transcribe, clip, title, caption.
Chain Desert Ant's Voz (transcribe with word timestamps), Clips (select the moments), and Title (name each clip) into a clipping engine that runs entirely on-device on iPhone or Mac, with word-accurate captions from Voz and no per-minute cost. Build it with the Desert Ant SDK. Voz (Swift). Install and API: https://desertant.com/docs/voz/. Clips (Swift). Install and API: https://desertant.com/docs/clips/. Title (Swift). Install and API: https://desertant.com/docs/title/. SDK source: https://github.com/Desert-Ant-Labs/desert-ant-core. Machine-readable catalog of every model and SDK: https://desertant.com/llms.txt.
What the model does
- Ranks a transcript's best non-overlapping moments: each clip gets scored and ranked. Build strong selections or unique editing features to pick the best sentences in video or audio recordings.
- Control the selection. Threshold on
percentile, not the raw score: a 0.8 cut averages 5 clips covering 17% of the video (highlights), a 0.3 cut averages 32 clips covering 74% (auto edit). - No context window: sentences run through the selector in batches and each candidate is scored on its own, so there's no context limit to work around. Create clips from long video or audio transcripts without any issues.
- Faster, better, cheaper. A 404-sentence, 25-minute transcript returns 12 clips in 9.19s on an iPhone 17 Pro and 10.22s on an iPhone 15 Pro; 2.78ms per candidate on the encoder alone.
- Multi-language support. 100 languages from one xlm-roberta-base trunk of 278M parameters: 284MB as a single int8 Core ML package on Apple.
- Pair Clips with our Title model to generate titles and descriptions and build a fully local clipping engine, that runs fully local.
Example app
Clipper
Built with Voz, Clips, Title
Generate short clips from a video podcast or a long recording, fully on device. A macOS app and a command-line tool over the same core.
Voz transcribes with a time on every word, Clips ranks the best spans, and Title writes a title and description for each.
macOS 26 or later, Apple Silicon
brew tap desert-ant-labs/tap
brew install --cask clipperGetting started
Add clip selection to your iOS or macOS app in a few lines of code. Clips docs.
// Swift Package Manager
.package(url: "https://github.com/Desert-Ant-Labs/desert-ant-core.git", from: "3.1.0")
// target dependency
.product(name: "Clips", package: "desert-ant-core")import Clips
let clips = Clips()
let moments = try await clips.clips(in: sentences) // [Clip], best first
for clip in moments {
print(clip.text, clip.start, clip.end, clip.percentile)
}Add Clips from Desert Ant Labs to this Swift project (iOS, macOS). What it does: Shorts and Highlights from any recording, on-device. SDK: Swift (iOS, macOS) Repo: https://github.com/Desert-Ant-Labs/desert-ant-core#readme // Swift Package Manager .package(url: "https://github.com/Desert-Ant-Labs/desert-ant-core.git", from: "3.1.0") // target dependency .product(name: "Clips", package: "desert-ant-core") Reference: - Model page: https://desertant.com/models/clips/ - Full catalog and other models: https://desertant.com/llms.txt Add the SDK, then follow its README for the exact API and current version. Do not invent API names or method signatures; confirm them against the README.
Specs
- Speed
- A 25-minute transcript in 9.19s on an iPhone 17 Pro, 10.22s on an iPhone 15 Pro
- On-device size
- 284MB int8 Core ML (Apple); two 283MB LiteRT files for Android, Linux, and Windows
- Languages
- 100
- Model
- xlm-roberta-base trunk, 278M parameters, four heads: saliency, start, end, clip score
- Platforms
- iOS 18, macOS 15, tvOS 18, visionOS 2 (Core ML). Android, Linux, and Windows LiteRT files are published but not supported in our SDK yet.
Clip edges are the weak spot. A clip can open on a pronoun whose referent was in the sentence before, fuse two topics, cut before the payoff, or swallow a sponsor read.
Short videos return few clips, a transcript under three sentences returns none, and the clip limit is a cap, not a quota. Non-Latin scripts are under-tested, and the Linux and Windows files are not supported in our SDK yet.
FAQ
What is Clips?
Clip selection that turns a long recording into ranked shorts and highlights from a transcript. On-device on iPhone or Mac.
Does Clips run on device?
Yes. Clips runs on the device, with no server call, so the data stays with the user.
Which platforms does Clips support?
Clips ships as a native on-device SDK for Swift.
How much does Clips cost?
Every model is free up to 100k monthly active devices per SDK. Unlimited inference per user. Contact us for custom licenses.
How accurate or fast is Clips?
Clips ranks a 25-minute transcript into 12 clips in 9.19s on an iPhone 17 Pro, on the device.