PreCog AI – Automatic AI Model Selection for Any Task
Hi HN, I'm one of the co-founders of PreCog AI, a project my friend and I started to make the best AI models more accessible. PreCog AI is a chatbot that automatically picks and answers with the best AI model for whatever task you throw at it. We made PreCog public on Monday and are getting great feedback. Originally built as an internal tool to help our small team reduce costs (paying for various chatbots) and get better AI output, PreCog has helped us so much with our workflow and ideation that we just had to share it. Key Features of PreCog - AI Model Matchmaking: With access to 18…
In plain words
PreCog AI is a chatbot that automatically selects and routes tasks to the most appropriate AI model from a library of 18 options. Designed for teams and individuals seeking better results across diverse applications like coding and creative writing, it aims to reduce costs and improve output quality by matching each query to the optimal model. The tool updates regularly based on the latest AI performance leaderboards.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hi HN, I'm one of the co-founders of PreCog AI, a project my friend and I started to make the best AI models more accessible. PreCog AI is a chatbot that automatically picks and answers with the best AI model for whatever task you throw at it. We made PreCog public on Monday and are getting great feedback. Originally built as an internal tool to help our small team reduce costs (paying for various chatbots) and get better AI output, PreCog has helped us so much with our workflow and ideation that we just had to share it. Key Features of PreCog - AI Model Matchmaking: With access to 18 models, PreCog automatically matches your questions with the most fitting AI model based on the task. - Versatile Adaptation: Works with any task, from coding to creative writing, giving you the right tool for the job. -Ongoing Updates: Stay current with AI advancements using the latest LLM leaderboard data (we are constantly adding and changing our leaderboard). See the leaderboard here - https://precog.ubik.studio/leaderboard -Preferred Model Selection: If you have a preferred model, choose it, and PreCog will use that model exclusively to respond. How PreCog Works: PreCog analyzes your query, references the model leaderboard, and then matches your query with the highest-ranked AI for that niche task. Delivering high-quality, task-specific output. PreCog's Model Leaderboard ranks AI models through over a million human comparisons, evaluated and presented on an Elo-scale. The dataset used to build the PreCog Leaderboard is from ChatBot Arena by https://lmarena.ai/. Researchers from UC Berkeley SkyLab and LMSYS developed the battle framework to produce the dataset. I love feedback, questions, and critiques it helps me and my friend develop with the user in mind. You can reach me at anytime at: [email protected]
More ai this month
the category →
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
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
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 · 26d ago · cactuscompute.com
Launched alongside, October 2024
the whole month →
Softr for Notion▲925Turn Notion databases into portals & apps with no code
Dev tools · 2024 · softr.io
One inbox for all your work discussions
Work · 2024 · generalcollaboration.com