A dense 65B preview model from ricursiveAI under Apache 2.0, built for agentic coding. Only every fifth layer (16 of 80) is global attention, and its cache is the one that grows: 64 KB per token, so a 32K window adds 1.9 GB and 128K adds about 8.5 GB. The other 64 layers use a 1,024-token sliding window, a fixed 0.4 GB in total, and the window is 2,097,152 tokens. AtomicChat's files named AD are larger than the plain type of the same name (its IQ2_XXS is 20.0 GB, 2.47 bits per weight). IQ1_M needs about 20.0 GB at 4K, comfortable on a 24 GB card. At IQ2_XXS it needs about 21.6 GB at 4K, tight on a 24 GB card. IQ2_S needs about 27.2 GB at 4K, comfortable on a 32 GB card. At Q4_K_M, the plain 38.8 GB file, it needs about 41.2 GB at 4K, comfortable on a 48 GB card. Sizes come from AtomicChat's GGUF files, and no per-level quality loss has been published.
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