Drilldown: Recipe

DeepSeek V4.1 Flash on 2x 8 GB (Project Maya) (1) · DeepSeek V4.1 Flash on 6x 8 GB (TP6) (1) · GLM 5.3 Flash on 2x 8 GB (ExLlamaV3 layer split) (1) · GLM 5.3 Flash on 2x 8 GB (Project Maya) (1) · Qwen3.8 Flash Next on 2x 8 GB (vektorprime PP2) (1) · Qwen3.8 Flash Next on 3x 8 GB (clee PP3) (1) · Qwen3.8 Flash Next on 3x or 4x 8 GB (zebgop-ops FP8 PP) (1)

DeepSeek-V4.1-Flash-1017 (1) · DeepSeek-V4.1-Flash-1017 (748B in the Maya README) (1) · GLM-5.3-Flash (320B MoE, 18B active) (1) · GLM-5.3-Flash (321B in the Maya README) (1) · Qwen/Qwen3.8-Flash-Next-FP8 (revision bcd9f01d) (1) · Qwen3.8-Flash-Next (2)

AWQ INT4: cyankiwi/Qwen3.8-Flash-Next-AWQ-INT4; 95 GiB BF16 PLE table in host RAM (FP8 table optional) (1) · EXL3 3.05 bpw: turboderp/GLM-5.3-Flash-exl3 (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) · Official block FP8, about 126 GiB including the about 50 GiB FP8 n-gram (PLE) table, which is served from host RAM; KV cache bf16 (the QSA layers refuse fp8) (1) · Official checkpoint: dense MXFP8 through an SM80 Marlin W8A16 path, routed experts MXFP4 through W4A16; KV FP8 (1) · W4A16 AutoRound: Intel/Qwen3.8-Flash-Next-W4A16-AutoRound; 95.4 GiB BF16 PLE table streamed from NVMe; KV fp8 e4m3 (software-decoded on SM80) (1)

Custom SM80 vLLM (patched from public commit 79a7108d9) (1) · ExLlamaV3 1.5.4 (built for SM80) with a small OpenAI-compatible server (1) · Project Maya (Strata and llama.cpp lineage) (1) · Project Maya (Strata and llama.cpp lineage, EXL3 loading, DFlash2 drafter) (1) · vLLM nightly + PR #53899 (a5530b9) + the repo's patch scripts (1) · vLLM nightly 7d0b4e57 plus the author's pure-Python fork clee/vllm-sm80 (branch q38fn/stack) (1) · vLLM: the vllm/vllm-openai:qwen38-flash-next image with zebgop-ops patches 0001 to 0016 (never 0008-WITHDRAWN) and three ported files (1)

None (1) · 0.1.dev1+ga5530b90c.d20260829 (1) · 0.1.dev20073+g8e685d198; repo commit 2f551bb (patch 0016, 2026-10-02) (1) · Flun/glm53-flash-cmp170hx-exl3 at 5933112 (1) · q38fn/stack on nightly-7d0b4e57 (1) · reports 0.0.0; patches/public-base-to-runtime.patch (109 files) (1) · v1.0.6 (this row) (1)

8 GB (7)

2 (4) · 3 (1) · 4 (1) · 6 (1)

engine-managed expert tiering across VRAM, host RAM and NVMe (1) · engine-managed split with expert tiering across VRAM, RAM and NVMe (1) · layer split (no tensor parallel), no P2P (1) · PP2 with PLE CPU offload (1) · PP3, no P2P (works at PP2 on two cards) (1) · PP4, VLLM_PP_LAYER_PARTITION=12,12,12,12, MTP 3, FULL_AND_PIECEWISE CUDA graphs; PCIe Gen2 x4 per card, no P2P. Three cards: PP3 with 16,17,15 or 16,16,16 (1) · TP6 (virtual-head padding), PP1 (1)

None (2) · 1,048,576 (1) · 1,048,576 (YaRN x4) (1) · 262,144 (1) · 262,144 native; 524,288 with YaRN 2.0; 1,048,576 with YaRN 4.0 (needle verified on PP3) (1) · 392,960 (profile q8_384k) (1)

60 - 63 (2) · 63 - 90 (5)

None (4) · 514 (1) · 4,831 (1) · 11,100 (1)

64 GB (2) · 64 GB, --gpu-memory-utilization 0.95 (1) · 64 GiB, gpu-memory-utilization 0.92 (1) · 64 GiB; --gpu-memory-utilization 0.94 plus per-rank KV budgets; measured 34.0-34.3 GiB per 12-layer rank, 37.9 GiB on the drafter rank (1) · 64 GiB; weights PP0 39.48 GiB, PP1 45.53 GiB; --gpu-memory-utilization 0.9 (1) · about 58 GiB of 64 GiB (116.6 GiB resident across both) (1)

None (6) · 200 W (1)

None (7)

None (6) · cmpunlocker VRAM unlock (64 GiB per card) (1)

Proven (2) · Reported (5)

68x0 (1) · c133 (1) · flipnburner (1) · pcsv. (1) · vektor_prime (1) · wgkbfcp (1) · ZackO2o (1)

August 2026 (1) · September 2026 (1) · October 2026 (4)

https://github.com/HalfVulpes/Deepinfer-SM80 · https://github.com/Morrowmake/dsv41-flash-cmp170hx-recipe · https://github.com/mw00/project-maya#how-fast-is-it · https://discord.com/channels/1518634379604136178/1518695289278566450/1561743826945843304 · https://discord.com/channels/1518634379604136178/1528826330454429706/1557523316120748073 · https://discord.com/channels/1518634379604136178/1528826330454429706/1560602001908170753 · https://github.com/344303947/dsv41-flash-pp5-170hx · https://github.com/alanoo81/deepseek-v41-flash-4x-cmp170hx · https://github.com/alexvnesta/glm53-flash-cmp170hx-tp · https://github.com/allover326/deepseek-v4-cmp170hx · https://github.com/anoane/09-deepseek-v41-flash-1017-exl3-tp5-1m · https://github.com/arvkmr/vllm-170hx-glm5 · https://github.com/clee/qwen3.8-flash-next-3x170hx · https://github.com/CurtisAccelerate/DeepSeekv41-Flash-1017-EXL3-CMP170HX · https://github.com/DUFRelic/qwen38-flash-next-recipe · https://github.com/ElectroHobo/mimo-v26-flash-cmp170hx-recipe · https://github.com/ElectroHobo/qwen38-flash-next-3bpw-1x-cmp170hx-recipe · https://github.com/ElectroHobo/qwen38-flash-next-w4a16-2x-cmp170hx-recipe · https://github.com/Flun/glm53-flash-cmp170hx-exl3 · https://github.com/GNmac-lab/deepseek-v41-flash-1017-cmp170hx · https://github.com/iIIusi0n/qwen3.8-flash-next-cmp170hx · https://github.com/kaka86mm/glm53-flash-170hx · https://github.com/mannydelrio/qwen38-flash-next-2x-cmp170hx · https://github.com/Morrowmake/glm53-flash-cmp170hx-recipe · https://github.com/Morrowmake/qwen38-flash-next-cmp170hx-recipe · https://github.com/nguyenthimy2022kg-alt/Qwen-Flash-SM80-170HX · https://github.com/promisezackr/glm53-flash-170hx-pp8 · https://github.com/tim-odonnell/cmp170hx-deepseek-v4-flash · https://github.com/vektorprime/qwen38-flash-next-pp2 · https://github.com/wgkbfcp/deepseek-v4.1-flash-1017-cmp170hx-recipe · https://github.com/Zanooda/deepseek-v4.1-flash-cmp170hx · https://github.com/zebgop-ops/qwen38-flashnext-pp · https://www.bozocentral.com/2x-cmp170hx-qwen3-flash-next · https://www.reddit.com/r/LocalLLM/comments/1w2f03e/qwen3827b_w4a16_on_one_64_gb_cmp_170hx_16070/ · Other · None