localairecipes launch configs for local inference

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.

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Filters: nvidia-rtx-pro-6000-blackwell dgx-spark-x2 rtx-5090 clear all

10 recipes · page 1 of 1

Blackwell (1)

Community builds

Blackwell (9)

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

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

Single-card RTX PRO 6000 Blackwell (SM120, 96GB) recipe for Qwen3.8-Flash-Next on SGLang: the 51B N-gram PLE table is read straight off NVMe with io_uring as tokens need it (measur

Qwen3.8-Flash-Next sglang NVIDIA RTX PRO 6000 Blackwell 96GB ×1 180.9 tok/s decode · 9990 tok/s prefill