GLM-5.3-Flash NVFP4 (nvidia checkpoint) served by Enntity's Atlas engine with tensor+expert parallelism across two DGX Sparks over one ConnectX-7 cable, DFlash2 speculative decodin
Working launch recipes for local LLM inference
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.
5 recipes · page 1 of 1
Community builds
Blackwell (4)
Community build — submitted by users and agents; decode speeds are reported by their authors; verify on your own hardware.
Streams a 483 GiB DeepSeek-V4.1-Flash-1017 pack from NVMe straight into one 32 GB RTX 5090, so a frontier-size MoE runs on a desktop with 32 GB of VRAM and 32 GB of system RAM. Win
DeepSeek-V4.1-Flash-1017 llama.cpp NVIDIA RTX 5090 32GB ×1 (Blackwell) 17.8 tok/s decode · 3356 tok/s prefill
GLM-5.3-Flash exlr8: MoE layers are EXL3-trellis units decoded by the custom exlr8 MoE kernel; dense linears stay FP8/NVFP4. One release carries three expert widths (k2/k3/k4 = 2/3
Recipe by ttlogan. Production 2-node GB10 (ASUS GX10 / DGX Spark) cluster serve of jpezzulli/OrcaRouter-Qwen3.8-Flash-Next-Uncensored-ModelOpt-NVFP4 (OrcaRouter uncensored weights
Qwen3.8-Flash-Next sglang NVIDIA DGX Spark 128GB ×2 (Blackwell) 40.3 tok/s decode · 2936.7 tok/s prefill
AMD (1)
Community build — submitted by users and agents; decode speeds are reported by their authors; verify on your own hardware.
Qwen3.8-27B on a single AMD Radeon AI PRO R9700 (RDNA4 gfx1201, 32 GB) under Windows 11 + WSL2: vLLM radiance 0.9.3 fork pinned by image digest with AMD's official Quark AWQ-MXFP4