Ant's trillion-parameter flagship has 7,000 downloads. Its smallest model has a million

InclusionAI, the open-source arm of Ant Group, publishes at both ends of the scale: trillion-parameter reasoning models and 16-billion-parameter models meant for a single accelerator. The download counters on Hugging Face show which end the world actually uses, and the gap is not close. As of 29 August 2026, LLaDA2.0-mini has been downloaded 1,013,751 times since its weights appeared on 25 November 2025. Ring-2.6-1T, the company's trillion-parameter reasoning flagship released on 14 May 2026, has 7,237. That is a ratio of roughly 140 to 1 in favour of the model that is about sixty times smaller. Size alone does not explain it, because the same pattern shows up inside each line — and in both cases it points backwards, to the older release. Ring-2.5-1T, the previous trillion-class model, has 175,004 downloads across 199 days, an average of 879 a day; its successor Ring-2.6-1T averages 68. Over the last 30 days the older model runs at 312 downloads a day and the newer one at 16, so the gap is widening rather than closing. In the diffusion line, LLaDA2.0-mini averages 3,673 downloads a day and its February successor LLaDA2.1-mini averages 1,429. The usual excuse — that a newer model has had less time to accumulate downloads — does not apply here, because these are daily rates measured from each model's own publication date. Nor is it a packaging problem: both trillion-class models ship natively in FP8 and contain the same number of FP8 parameters, 1,009,494,523,904. Neither is resold by a single provider on OpenRouter. An earlier suspicion, that only the older one was documented in the official SGLang deployment cookbook, turns out to be wrong: the cookbook lists Ring-2.5-1T and Ring-2.6-1T alike. One caveat on the counters themselves. Hugging Face reports both a 30-day figure and a lifetime figure, and only the lifetime figure allows a fair comparison across models with different release dates; the widely quoted 30-day number makes any recent release look weak by construction. Downloads also measure trial and tooling traffic, not production use — a file pulled by a benchmarking script counts the same as one pulled by a company. What the numbers do suggest is that for open weights, the constraint is hardware, not capability. A model that fits on one accelerator gets tried; a model that needs a rack gets read about. The catalogue has today added a profile of LLaDA2.0-mini, the most downloaded model this publisher has ever released.