99% of slop *does not* come from AI
it comes from Humans, who have bad taste
current AI models can build anything
but it's up to YOU to know what to build
if you suck at Product, no agent will save you
The Rio 3.5 model broke the internet this week. The plot twist? Itโs essentially our open-source model, Nex N2 Pro, wearing a different hat.
๐คฏ We analyzed the weights, and the recipe is exact: Rio 3.5 โ 0.6 * Nex N2 Pro + 0.4 * Qwen 3.5
It even literally introduces itself as "Nex N2 Pro" if you ask it without initial system prompt!
๐ We are flattered that the City of Rio used our work to achieve SOTA performance. Thanks for the ultimate benchmark validation.
๐ค But in the open-source world, attribution matters.
๐ Full mathematical proof & verify script in the first reply!
1) Our team at Meta has a tough new coding benchmark challenging models to code entire programs including ffmpeg and the PHP compiler from scratch.
2) Top accuracy is 0%
3) We will be making the benchmark harder.
Introducing SubQ - a major breakthrough in LLM intelligence.
It is the first model built on a fully sub-quadratic sparse-attention architecture (SSA),
And the first frontier model with a 12 million token context window which is:
- 52x faster than FlashAttention at 1MM tokens
- Less than 5% the cost of Opus
Transformer-based LLMs waste compute by processing every possible relationship between words (standard attention).
Only a small fraction actually matter.
@subquadratic finds and focuses only on the ones that do.
That's nearly 1,000x less compute and a new way for LLMs to scale.