inclusionAI's Ling-3.1-flash (Ant Group), released in October under MIT: a 560B mixture-of-experts reasoning model with 25B parameters active per token. It is aimed at agents, coding and long office tasks. Only 9 of its 72 layers keep a growing cache, and those store MLA's compressed vectors, so even its full 256K window adds only about 3 GB: the weights decide where it runs. At Q4_K_M it needs about 371 GB at 4K context, more than any single GPU in this index. The 512 GB Mac Studio gives its GPU about 384 GB, which holds it only tightly on this site's rule; on servers the vendor's reference setup is eight H200s or four GB300s running FP8. Q8_0 needs about 628 GB. The vendor quotes a 1M-token window, but the released config sets 262,144 positions with no scaling, so that is the limit used here. llama.cpp runs it as bailingmoe3 from build b11571. Sizes come from a published GGUF file, whose maker reports KL divergence rather than perplexity, so no quality-loss figure is shown.
I Haunted My Own Terminal Using Local Open-Weight LLMs and Ollama