
Anti-Gravity: Private AI PDF
Local AI PDF Editor. 100% Private. Zero Cloud. Elite.
What it does
Anti-Gravity is the world's first "Zero-Cloud" AI PDF workspace. Built for elite professionals, it brings neural document intelligence (summarization, chat, OCR) directly to your device. No cloud uploads, no data training, and no sneaky subscriptions. Just powerful, bank-grade privacy with a premium dark aesthetic
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Google Antigravity CLIMay 2026 · antigravity.google · ▲250Run coding agents directly from your terminal

- OAOpenGravity – A zero-install, BYOK vanilla JS clone of AntigravityMay 2026 · github.com · ▲106
Hi. I’m a high school student studying for my GCSEs. I was using Google Antigravity heavily for my side projects, but I kept hitting the usage limits, and getting random "agent terminated" errors. So I decided to try build my own version of the IDE. I love the UI, so I copied it as accurately as possible, and then hooked up some logic into it, including the INCREDIBLY finicky webcontainer api. I tried to keep it super lightweight, no build steps, or dependencies, and now that its open source, I'm hoping people can build things on top of it that arent possible with closed source tools, like…
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com

