AI Breakthroughs
Renmin and Ant Group train LLaDA MoE v2 with diffusion scaling laws
By Arjun
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13 Aug 10:03 AM
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Via arXiv
Researchers at Renmin University of China and Ant Group posted LLaDA MoE v2, a 30 billion parameter mixture-of-experts diffusion language model that activates about 3 billion parameters per token. Guided by new MoE diffusion scaling measurements, they trained it from scratch on 23.5 trillion tokens and report approaching Qwen3 on several benchmarks with roughly 65 percent as many pretraining tokens. After supervised fine-tuning alone, they say it beats SDAR Chat on seven of eight reasoning and coding tests. That matters as Chinese labs push parallel diffusion decoding. The caveat is that the paper is an arXiv preprint pending independent replication and open weights.
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