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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23 recipes · page 1 of 2

Ampere (1)

Community builds

Blackwell (4)

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

DeepSeek-V4.1-Flash-1017 at TP3 on three 96 GB RTX PRO 6000 Blackwell cards with the full 1M-token context, serving DeepSeek's original weights (FP8 dense + MXFP4 routed experts, n

DeepSeek-V4.1-Flash sglang NVIDIA DGX Spark 128GB ×4 (Blackwell) 89.7 tok/s decode · 5398 tok/s prefill

Ampere (6)

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

Qwen3.8-Flash-Next (125B MoE) 3 bpw AutoRound experts on ONE CMP 170HX card with the full 262,144-token context: 197.8/296.4/135.5 tok/s one user (structured/code/prose), 371 tok/s

Tensor-parallel successor to Flun's 2x CMP 170HX layer-split recipe: ExLlamaV3 TP2 over both 64 GB cards with a 655,360-token Q8 KV pool (392,960-token request cap), DFlash2 K7 spe

GLM-5.3-Flash exllamav3 NVIDIA CMP 170HX 64GB ×2 (Ampere) 123.6 tok/s decode · 1316 tok/s prefill

First ExLlamaV3 serving recipe on 2x CMP 170HX: full-VRAM HBM-resident GLM-5.3-Flash EXL3 3.05bpw (~116.6 GiB across 2x64GB, no CPU/SSD tier) with DFlash2 K7 speculative decoding —

GLM-5.3-Flash exllamav3 NVIDIA CMP 170HX 64GB ×2 (Ampere) 90 tok/s decode

Qwen3.8-Flash-Next (125B MoE) INT4-expert W4A16 on two CMP 170HX cards, full 262,144-token context: 241/350/198 tok/s one user (structured/code/prose), 495 tok/s editing code, 895/

DeepSeek-V4.1-Flash-1017 (748B MoE) on four CMP 170HX cards power-capped at 180 W, with the model's 189 GiB Engram n-gram tables streamed from NVMe on demand. Recipe 1.2.0 (author

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

Qwen3.8-27B vllm AMD Radeon AI Pro R9700 32GB ×1 115 tok/s decode · 2762 tok/s prefill

Showing 12 of 23 recipes on this page — filter or paginate for the rest.