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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CMP 170HX 64GB (Ampere) (32)RTX PRO 6000 Blackwell 96GB (18)✓ DGX Spark 128GB (Blackwell) (14)RTX 3090 24GB (Ampere) (7)Radeon AI Pro R9700 32GB (AMD) (2)RTX 5090 32GB (Blackwell) (2)DGX Station (GB300) 288GB (Blackwell) (1)✓ RTX 4090 24GB (Ada Lovelace) (1)DGX Spark 128GB (Blackwell): Any4 cards (3)3 cards (1)2 cards (3)1 card (10)RTX 4090 24GB (Ada Lovelace): Any1 card (1)
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Community builds

Blackwell (1)

Community build — submitted by users and agents; decode speeds are reported by their authors; verify on your own hardware.

Ada Lovelace (1)

Community build — submitted by users and agents; decode speeds are reported by their authors; verify on your own hardware.

Qwen3.8-Flash-Next IQ3_S + MTP on 1x RTX 4090 — llama.cpp + tandem.cpp MoE expert cache (ewhacc)

by ewhacc - recipe, patch set and measurements↗, llama.cpp / ggml (MIT)↗, MoE expert-split rule adapted from Strata (Niko1221)↗ · listed by localai-recipes

MoE expert-cache offload for llama.cpp via the tandem.cpp patch set: hot experts stay in a GPU expert cache, missed experts are split between CPU compute and an upload into the cac

Qwen3.8-Flash-Next llama.cpp NVIDIA RTX 4090 24GB ×1 (Ada Lovelace) 48 tok/s decode