Qwen3.6 27B PRISM PRO — DQ GGUF llama.cpp native GGUF quantization of Qwen3.6 27B PRISM PRO using the PRISM project's dynamic quant (DQ) recipe. ~13.7 GB (vs 55 GB BF16). PRISM PRO of Qwen/Qwen3.6 27B (bias/propoganda removal) This GGUF preserves the model's native MTP draft head + full vision tower, and pairs with the separately published EAGLE 3 drafter for lossless faster decode. Performance llama.cpp on a single NVIDIA Blackwell GPU, single stream greedy decode: config tok/s speedup : : no spec baseline 80 1.00× native MTP (built in draft head) 121 1.51× EAGLE 3 chain (with our drafter) 111 1.39× Speculative decoding is lossless (output token identical to non spec greedy, modulo batched verify floating point non associativity intrinsic to all spec decoding). For a faster SGLang deployment (~183 tok/s, ~1.97× over no spec) using the BF16 target + EAGLE 3, see the drafter repo. Quick start (llama.cpp) Provenance Base: Qwen/Qwen3.6 27B (hybrid: 48 GatedDeltaNet linear attention layers + 16 full attention layers; hidden 5120; vocab 248 320; native MTP head). PRISM Dynamic Quantization: PRISM DQ recipe (llama.cpp GGUF dynamic quant) — preserves the MTP draft head (15 tensors) and th…
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