Model releases & benchmarks
LLaDA MoE v2: Scaling Mixture-of-Experts Diffusion Language Models
The abstract reports that MoE diffusion language models do not simply inherit autoregressive scaling trends: optimization, data allocation, and expert-pool preferences differ.
Why it matters: The reported differences give practitioners scaling guidance specific to MoE dLLMs rather than assuming AR-model trends transfer directly. The benchmark results are selective comparisons, not evidence of general capability or cost equivalence.