The AI hub.
OLUD INDEX—Open-source and commercial AI side by side — projects, models, alternatives, releases and pricing, measured. Rebuilt every day, new releases within the hour.
Today in AI
This week on the blog
We measured 10,491 open-source AI projects. 42% have gone quiet.
4,436 of the 10,491 projects in the olud.ai catalogue — 42.3% — have not seen a push in six months, and 3,562 have been silent for more than a year. Fame does not protect a repo: among the 1,150 projects with 10,000+ stars, 197 are quiet too.
The intelligence gap is 5%. The price gap is 3×.
Across 270 models with a benchmark and a price, the best open model scores 59.7 against 63.1 — and costs 3.1× less per point of intelligence.
What actually runs on your GPU in 2026 — the honest table
A 24 GB card runs a 35B model ; an 8 GB card runs Qwen3 8B in an estimated 6.4 GB. The VRAM table for the models people actually download — margin ±40%.
700 MCP servers, mapped: where AI agents are really going
36.4% of MCP servers fit no established category, 22.4% are aggregators — and the largest single-purpose category is Memory & Knowledge. Agents are getting memories before hands.
Why olud.ai ?
One live hub for the whole AI landscape — open-source and commercial, measured every day and watched hourly for new releases, so you never miss what ships.
Your project already has a page. Take it.
Every open-source AI project we track gets its own page, rebuilt every day and translated into six languages. If you maintain one of them, claiming it takes about a minute: sign in with GitHub and it confirms the repo is yours. No commit to push, no token to store, no write access, no card.
Seven live panels in one screen: GitHub momentum, model price changes, project health, ELO rankings and the latest releases — refreshed continuously.
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