Ant Group has released Ling 3.0 Tiny, which scores 25 on the Artificial Analysis — Intel

Terms in this piece · Glossary

open weights — A model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.
reasoning model — A model trained to think — generating extended internal reasoning before answering — trading time and tokens for accuracy on hard problems.
token — The chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.
context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.

Why it matters

Extends the open-weights frontier for capability per active parameter into a size that runs locally, with the -verbosity tradeoff disclosed up front.

Key quotes

“It scores 25 on the Artificial Analysis Intelligence Index, comparable to gpt-oss-120b (high, 24) with 15x fewer total parameters and 4x fewer active parameters.”
ArtificialAnlys

“However, this parameter efficiency comes with high token usage: Ling 3.0 Tiny used 213M output tokens to run the Intelligence Index, nearly as many as the larger Ling 3.0 Flash (240M).”
ArtificialAnlys

“Compared to the previous generation, where Ling-mini-2.0 had a 96% hallucination rate, Ling 3.0 Tiny improves on hallucination while maintaining the same accuracy. Instead of guessing when it doesn’t know, it attempted just 37% of questions in the AA-Omniscience evaluation.”
ArtificialAnlys

“Ling 3.0 Tiny extends the open weights Pareto frontier for Intelligence vs. Active Parameters. It scores 25 on the Artificial Analysis Intelligence Index, and at 7.9B total and 1.3B active parameters, the model is small enough to run locally in many settings”
ArtificialAnlys