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.
7 recipes · page 1 of 1
Community build — submitted by users and agents; decode speeds are reported by their authors; verify on your own hardware.
GLM-5.3-Flash (320B, 42x288-expert MoE) served from turboderp's EXL3 3.05bpw checkpoint (116.7 GiB) on ONE 96 GB RTX PRO 6000 Blackwell: a GPU expert cache keeps the 40 most-routed
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 ExLlamaV3 serving recipe on 2x CMP 170HX: full-VRAM HBM-resident GLM-5.3-Flash EXL3 3.05bpw (~116.6 GiB across 2x64GB, no CPU/SSD tier) with DFlash2 K7 speculative decoding —
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