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) (31)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)CMP 170HX 64GB (Ampere): Any6 cards (1)4 cards (10)3 cards (2)2 cards (15)1 card (3)RTX 3090 24GB (Ampere): Any4 cards (2)2 cards (4)1 card (3)
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2 recipes · page 1 of 1

Ampere (1)

Community builds

Ampere (1)

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

GLM-5.3-Flash EXL3 3.05bpw on 2x RTX 3090 — vLLM + ExLlamaV3 CPU expert offload, 256K (DominikBucko)

by DominikBucko↗, turboderp-org (EXL3 quant + ExLlamaV3)↗, spele1100 (GLM-5.3 vLLM overlay)↗ · listed by localai-recipes

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

GLM-5.3-Flash vllm NVIDIA RTX 3090 24GB ×2 (Ampere) 48.2 tok/s decode · 1106 tok/s prefill