Engine configs (vLLM, SGLang, llama.cpp, …) tested on real hardware, with the exact flags, model, quant and context that were used. Copy one, run it, or hand it to your agent. Search or refine below; every recipe on the site is listed here.
12 recipes · page 1 of 1
Single-card Blackwell recipe for Qwen3.8-Flash-Next (hybrid GDN/QSA MoE, 48 layers, 512 experts) on one 96 GB RTX PRO 6000: the Community image community image R34 (localinferencel
PP4 (pipeline-parallel 4, TP1) as-run on a 4x CMP 170HX rig 2026-09-28 at --gpu-memory-utilization 0.93 after 0.95 OOM-killed warmup (a 72 MiB KDA prefill workspace did not fit in
Community build — submitted by users and agents; decode speeds are reported by their authors; verify on your own hardware.
DeepSeek-V4.1-Flash-1017 at TP3 on three 96 GB RTX PRO 6000 Blackwell cards with the full 1M-token context, serving DeepSeek's original weights (FP8 dense + MXFP4 routed experts, n
Recipe by Alex Ellis / OpenFaaS Ltd. GLM-5.3-Flash (320B-A18B, NVFP4) served tensor-parallel 4 across four DGX Spark (GB10, sm_121) nodes cabled as a closed switchless RoCE ring: t
Local Inference Lab production two-card serving config: TP2/DCP2, 8 concurrent seqs, MTP3 on B12X, lossless-CSF NVFP4 MoE (MXFP8-CSF-QAD weights, 188.87 GB), online MXFP8 attention
Community build — submitted by users and agents; decode speeds are reported by their authors; verify on your own hardware.
Four native active sequences on two 64 GiB CMP170HX cards; GLM-5.3-Flash EXL3 3.05bpw, TP2, with the Weightless GLP44 steering vector at alpha 2, FP16 recurrent state, Q8 GPU KV, D
Four native active sequences on two 64 GiB CMP170HX cards; GLM-5.3-Flash EXL3 3.05bpw, TP2, with the Weightless GLP44 steering vector at alpha 2, FP16 recurrent state, Q8 GPU KV, D
Four native active sequences on two 64 GiB CMP170HX cards; GLM-5.3-Flash EXL3 3.05bpw, TP2, with the Weightless GLP44 steering vector at alpha 2, FP16 recurrent state, Q8 GPU KV, D
Tensor-parallel successor to Flun's 2x CMP 170HX layer-split recipe: ExLlamaV3 TP2 over both 64 GB cards with a 655,360-token Q8 KV pool (392,960-token request cap), DFlash2 K7 spe
First EXL3 row for Qwen3.8-Flash-Next and first Morrowmake QFN lane: turboderp/Qwen3.8-Flash-Next-exl3 (EXL3 5.05 bpw) on two CMP 170HX cards (TP2, whole routed experts per card, P
GLM-5.3-Flash (turboderp EXL3 3.05bpw) tensor-parallel on 2x RTX 3090 24 GB + 128 GB system RAM: vendor vLLM image with the spele1100/vllm-glm53 GLM-5.3 overlay, ExLlamaV3 @ 499890
Community build — submitted by users and agents; decode speeds are reported by their authors; verify on your own hardware.
27B Qwen served from a single podman-compose stack on two Radeon AI PRO R9700 (gfx1201) cards: vLLM runs the prebuilt stilldeadcode/vllm-radiance:0.9.3 image (RDNA4 patches + tuned