https://llmobile.news/companies/desert-ant-labs/A concise news ticker covering AI on mobile devices, local models, apps and hardware.en-GBhttps://llmobile.news/ticker/desert-ant-labs/https://llmobile.news/ticker/desert-ant-labs/Tue, 08 Sep 2026 00:00:00 +0200Desert Ant Labs, a newly launched company, has introduced 18 on-device models as its first release, each built for a single task such as transcription, audio enhancement, personal data masking, language detection and video summarization, according to its launch post. Twelve of the models are stable and six are in beta. The first collection of Desert Ant Labs models, as shown in the launch post.Desert Ant Labs Voz, the transcription model, converts 10 minutes of audio in 2 seconds on an iPhone, according to the company. Desert Ant Labs reports 298x realtime speed on an iPhone 17 Pro and 319x on an M3 Ultra, and says Voz is 4.7x faster than Whisper and returns word-level timestamps. The audio enhancement model Clear is 9 MB and processes a 5-minute recording in 1 second, at 302x realtime on an iPhone 16 Pro and 345x on a MacBook Pro with M5. Redact masks personal data in 27 languages, takes up 12 MB and detects 88.8% of personal data, the company says. Tongue identifies 84 languages in 2 MB and reaches an accuracy of 0.933 from three words. Clips turns a 10-minute video into clips in 5 seconds with a 284 MB model, which Desert Ant Labs says is 10x faster than Claude Sonnet and uses 470x less energy at the same quality. All models are free up to 100k monthly active devices, with no tokens and no logins, according to the Desert Ant Labs website. Developers integrate them through SDKs for Swift, Kotlin and JavaScript, which are published on GitHub. The models are also on Hugging Face, where browser demos let users try them, and the company also offers a command-line tool for testing. Documentation is at desertant.com/docs. Source: https://desertant.com/blog/introducing-desert-ant-labs/ Read the article: https://llmobile.news/ticker/desert-ant-labs/Developer toolsBenchmarksApple