Ant Group has released Ling 3.0 Tiny, which scores 25 on the Artificial…
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Ant Group has released Ling 3.0 Tiny, which scores 25 on the Artificial Analysis Intelligence Index. With just 7.9B total and 1.3B active parameters, it sits on the Pareto frontier for Intelligence vs. Active Parameters @AntLingAGI has released Ling 3.0 Tiny, an open weights reasoning model with a 262K-token context window. 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. 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). It follows the recent release of Ling 3.0 Flash, which scores 38 with 124B total and 5.1B active parameters. The weights are available on Hugging Face under an MIT license. Key results: ➤ 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 ➤ Ling 3.0 Tiny makes a 59-point improvement in AA-Omniscience over…
- 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.
Extends the open-weights frontier for capability per active parameter into a size that runs locally, with the -verbosity tradeoff disclosed up front.
“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
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