Open-Source AI & Open Models Reading List

Nathan Lambert · 11 Sept 2026 · interconnects.ai ↗

3 korrents from this piece

Nathan Lambert did not write this page.

Every claim below was made in this piece, quoted word for word and numbered in the order the piece makes them, so you can read it there rather than take our word for it. The sentence above each quote is our reading of the claim, not their wording. Each quote was checked against a stored copy of the page at build time; where the two differ, the quote is the fact.

Our reading
The performance gap between open and closed AI models has narrowed to roughly 4-6 months.

Their wordsThe open-closed model gap has reduced in recent years, and is now at roughly 4-6 months.
Our reading
Since 2024, the leading open-weight AI models have come from Chinese labs rather than American ones.

Their wordsThe leading open models have all come from Chinese labs since ~2024.
Our reading
Distillation is the most significant debate surrounding open AI models in 2026.

Their wordsDistillation - the process of training on output tokens from another model - is the single most eventful debate around open models in 2026.