My Open Source Deep Research tools beats Google and I can Prove it
Solo Dev. Couch Potato. Build a Standalone Open Source Deep research tool. And it Beats Google , Open ai and Perplexity in Multible Metrics : https://veritas-test.neocities.org/ ( pls translate it its german) Guys : lets get this to be used. Because KNOWLAGE Shouldnt be locked behind Paywalls
In plain words
My Open Source Deep Research tools is a standalone, open-source research application built by a solo developer. It functions as a deep research tool accessible to anyone without paywalls. The software is designed for users seeking free alternatives to commercial research platforms. The creator emphasizes accessibility and knowledge sharing as core principles behind the project's development.
written from the facts on this page · September 2026
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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.
AI · 17d ago · simedw.com
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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
