Drilldown: Recipe
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& source :
https://github.com/Morrowmake/glm53-flash-cmp170hx-recipe or
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& source :
https://github.com/Morrowmake/glm53-flash-cmp170hx-recipe or
Other Use the filters below to narrow your results.
page:
DeepSeek V4.1 Flash heretic on 4x 8 GB (1) ·
DeepSeek V4.1 Flash on 2x 8 GB (Project Maya) (1) ·
DeepSeek V4.1 Flash on 4x 8 GB (CurtisAccelerate TC-MoE) (1) ·
DeepSeek V4.1 Flash on 6x 8 GB (Deepinfer-SM80 TP2 x PP3) (1) ·
DeepSeek V4.1 Flash on 6x 8 GB (TP6) (1) ·
DeepSeek V4.1 Flash on 8x 8 GB (Deepinfer-SM80 TP4 x PP2) (1) ·
GLM 5.3 Flash on 2x 8 GB (ExLlamaV3 layer split) (1) ·
GLM 5.3 Flash on 2x 8 GB (Project Maya) (1) ·
GLM 5.3 Flash on 3x 8 GB (1) ·
GLM 5.3 on 8x 8 GB (Int4-Int8Mix PP8) (1) ·
GLM 5.3 on 8x 8 GB (vllm-170hx-glm5) (1) ·
Qwen3.8 27B on 1x 8 GB (W4A16 vLLM) (1) ·
Qwen3.8 Flash Next on 2x 8 GB (Morrowmake EXL3) (1) ·
Qwen3.8 Flash Next on 2x 8 GB (Plean PP2) (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 4x 8 GB (1)
model:
DeepSeek-V4.1-Flash-1017 (4) ·
DeepSeek-V4.1-Flash-1017 (748B in the Maya README) (1) ·
DeepSeek-V4.1-Flash-1017 heretic (pqhaz abliteration) (1) ·
GLM-5.3 (full 78-layer DSA MoE, not Flash) (1) ·
GLM-5.3 (full 78-layer, not Flash) (1) ·
GLM-5.3-Flash (320B MoE, 18B active) (2) ·
GLM-5.3-Flash (321B in the Maya README) (1) ·
Qwen3.8-27B (dense) (1) ·
Qwen3.8-Flash-Next (5)
quant:
AWQ INT4: cyankiwi/Qwen3.8-Flash-Next-AWQ-INT4; 95 GiB BF16 PLE table in host RAM (FP8 table optional) (1) ·
AWQ W4A16: wtdcode/Qwen3.8-Flash-Next-AWQ-W4A16 (1) ·
EXL3 3.05 bpw: turboderp/GLM-5.3-Flash-exl3 (1) ·
EXL3 5.05 bpw; PLE (n-gram) table read from SSD (1) ·
GLM-5.3-Int4-Int8Mix (INT4 / INT8 mix); KV fp8_ds_mla (1) ·
GLM-5.3-Int4-Int8Mix-AWQ-g64; drafter incoai/GLM-5.3-DFlash2 (1) ·
Hybrid: LibertAI EXL3 2.9 bpw routed experts (layers 0-39), official FP8/FP4 for attention, shared experts, head, draft and Engram; KV fp8_ds_mla (1) ·
Hybrid: routed experts EXL3 2.9 bpw (LibertAIDAI), everything else official FP8/BF16 with the 38 heretic attn.wo_b tensors (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) ·
Official checkpoint (FP8 dense, FP4 experts); software FP8 on sm_80 (2) ·
Official checkpoint: dense MXFP8 through an SM80 Marlin W8A16 path, routed experts MXFP4 through W4A16; KV FP8 (1) ·
W4A16 (INT4 weights, Marlin kernels) (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) ·
W4A16, about 4.3 bpw, 163 GiB on disk (1)
engine:
Custom SM80 vLLM (patched from public commit 79a7108d9) (1) ·
ExLlamaV3 1.5.4 (built for SM80) with a small OpenAI-compatible server (1) ·
Morrowmake/vllm-cmp170hx (bind-mounted sm80 package) plus the author's tensor-core MoE kernels (1) ·
Morrowmake/vllm-cmp170hx (EXL3 path) (1) ·
Morrowmake/vllm-cmp170hx (via the glm53-flash-cmp170hx-recipe) (1) ·
Morrowmake/vllm-cmp170hx (vLLM fork, container image) (1) ·
Morrowmake/vllm-cmp170hx branch ampere-glm53 plus fail-closed source patches (1) ·
Project Maya (Strata and llama.cpp lineage) (1) ·
Project Maya (Strata and llama.cpp lineage, EXL3 loading, DFlash2 drafter) (1) ·
vLLM (1) ·
vLLM (build not stated) (1) ·
vLLM 0.29.1rc1 nightly plus the checkpoint author's patches (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 PR #56201 head (79a7108d) plus the two Deepinfer-SM80 patches and 30 drop-in modules (2) ·
wtdcode/vllm-backport (image lazymio/vllm-backport:latest-sm80) (1)
engine version:
None (4) ·
0.1.dev1+ga5530b90c.d20260829 (1) ·
Deepinfer-SM80 2a828fc lineage; vLLM v0.28.1rc0 base (1) ·
Deepinfer-SM80, vLLM v0.28.1rc0 base (1) ·
Flun/glm53-flash-cmp170hx-exl3 at 5933112 (1) ·
latest-sm80 tag as of 2026-10-16 (1) ·
not stated (1) ·
q38fn/stack on nightly-7d0b4e57 (1) ·
recipe 1.0.0 (commit d4d1f525), engine a0c57b52 (1) ·
reports 0.0.0; patches/public-base-to-runtime.patch (109 files) (1) ·
tag qwen38-recipe-1.0.0, engine 18305948ac (1) ·
v1.0.6 (this row) (1) ·
vLLM 0.30.1rc1, fork commit 378c37b0 (1) ·
vllm-cmp170hx 18305948ac; TC-MoE fb9786ec (1)
cards:
topology:
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) ·
PP2, MTP 3, no P2P (1) ·
PP3 (1) ·
PP3, no P2P (works at PP2 on two cards) (1) ·
PP8 (also PP9 and PP10), TP1 (1) ·
PP8, TP1 (1) ·
single card (1) ·
TP2 with expert parallel (1) ·
TP2 x PP3, partition 14,14,12 (1) ·
TP4 (1) ·
TP4 with expert parallel, MTP 3 (1) ·
TP4 x PP2, partition 20,20 (1) ·
TP4, peer access off (NCCL_P2P_DISABLE=1), host all-reduce (1) ·
TP6 (virtual-head padding), PP1 (1)
context:
None (2) ·
1,000,000 (YaRN x4 from 262,144) (1) ·
1,048,576 (4) ·
1,048,576 (YaRN x4) (1) ·
1,048,576 per request (1) ·
262,144 (3) ·
262,144 (256K in the post) (1) ·
262,144 (weights address 1,048,576) (1) ·
262,144 native (YaRN to about 500k in the recipe's long variant) (1) ·
392,960 (profile q8_384k) (1) ·
about 1,000,000 (8-bit KV cache) (1)
decode tps:
prefill tps:
vram per card:
64 GB (5) ·
64 GB, --gpu-memory-utilization 0.95 (1) ·
64 GiB (2) ·
64 GiB, --gpu-memory-utilization 0.92 (miner co-resident) (1) ·
64 GiB, --gpu-memory-utilization 0.95 (2) ·
64 GiB, --gpu-memory-utilization 0.97 (1) ·
64 GiB, gpu-memory-utilization 0.92 (1) ·
64 GiB, GPU_UTIL 0.96 at PP8 (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) ·
about 62.5 GB used of 64 GB, --gpu-memory-utilization 0.97 (1)
power cap:
driver:
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Showing below up to 17 results in range #1 to #17.