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.

Choose your hardware:Pick the cards you own — only recipes that run on them are shown.
✓ 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)DGX Station (GB300) 288GB (Blackwell) (1)✓ RTX 5090 32GB (Blackwell) (1)CMP 170HX 64GB (Ampere): Any6 cards (1)4 cards (10)3 cards (2)2 cards (15)1 card (3)RTX PRO 6000 Blackwell 96GB: Any4 cards (5)3 cards (1)2 cards (5)1 card (7)RTX 5090 32GB (Blackwell): Any2 cards (1)
Refine

Source:

Engine
Model
Quant
Storage requirement
Feature tags

Reset

Filters: rtx-5090-x2 rtx-pro-6000-blackwell 170hx-x6 vision clear all

3 recipes · page 1 of 1

Blackwell (1)

Community builds

Blackwell (2)

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

GLM-5.3-Flash EXL3 2.05bpw on 2x RTX 5090 - TabbyAPI hot-expert swaps, 262K ctx, vision

by adrienbrault (recipe, five patch overlays, measurements)↗, zai-org (GLM-5.3-Flash)↗, turboderp (EXL3 2.05bpw quantisation; ExLlamaV3 + CPU MoE offload)↗, theroyallab (TabbyAPI)↗, adrienbrault/qwen3.8-flash-next-2x-rtx5090 (base image: ExLlamaV3 dev 5783a93 patch stack + TabbyAPI 53da7919)↗ · listed by localai-recipes

GLM-5.3-Flash (321B MoE, ~18B active) turboderp EXL3 2.05bpw on two RTX 5090 + 64 GB DDR5: TabbyAPI on ExLlamaV3 with CPU-offloaded routed experts (96/layer GPU0 layers 3-22+MTP, 1

GLM-5.3-Flash exllamav3 NVIDIA RTX 5090 32GB ×2 (Blackwell) 62.9 tok/s decode · 2023 tok/s prefill