Drilldown: Recipe
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AWQ W4A16: wtdcode/Qwen3.8-Flash-Next-AWQ-W4A16 (1) ·
Maya GGUF (Maya-S 340 GB or Maya-XS 277 GB; Engram tables stay on SSD) (1) ·
Maya-M GGUF (116 GB), every expert in VRAM; Maya-S (96.5 GB) and Maya-S24 (94.7 GB) also reported (1) ·
Mixed INT4 AutoRound (Minachist/Qwen3.8-Flash-Next-INT4-Mixed-AutoRound, about 65 GB) with the full BF16 PLE table on NVMe (1) ·
W4A16 (INT4 weights, Marlin kernels) (1) ·
W4A16: halt95/Qwen3.8-Flash-Next-W4A16-Merlin (AutoRound INT4 g128 experts, INT8 GDN projections, FP8 n-gram table) (1)
Morrowmake/vllm-cmp170hx image (Qwen EXL3 release) with patch files mounted read-only (1) ·
Project Maya (Strata and llama.cpp lineage) (1) ·
Project Maya (Strata and llama.cpp lineage, EXL3 loading, DFlash2 drafter) (1) ·
vLLM (1) ·
vLLM 0.29.1rc1 nightly plus the checkpoint author's patches (1) ·
wtdcode/vllm-backport (image lazymio/vllm-backport:latest-sm80) (1)
https://discord.com/channels/1518634379604136178/1528826330454429706/1560602001908170753 (1) ·
https://github.com/ElectroHobo/qwen38-flash-next-w4a16-2x-cmp170hx-recipe (1) ·
https://github.com/mw00/project-maya#how-fast-is-it (2) ·
https://www.bozocentral.com/2x-cmp170hx-qwen3-flash-next (1) ·
https://www.reddit.com/r/LocalLLM/comments/1w2f03e/qwen3827b_w4a16_on_one_64_gb_cmp_170hx_16070/ (1)
Showing below up to 6 results in range #1 to #6.


