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: radeon-ai-pro-r9700-x2 170hx rtx-3090 dgx-spark clear all

17 recipes · page 1 of 2

Community builds

Blackwell (8)

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

Qwen3.8-Flash-Next (~180B multimodal MoE, NVFP4) on one NVIDIA DGX Spark (GB10, 121 GiB unified memory) with a pinned vLLM nightly image + 14 provenance-tracked patches (patch --fu

Ampere (3)

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

AMD (1)

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

27B Qwen served from a single podman-compose stack on two Radeon AI PRO R9700 (gfx1201) cards: vLLM runs the prebuilt stilldeadcode/vllm-radiance:0.9.3 image (RDNA4 patches + tuned

Qwen3.8-27B vllm AMD Radeon AI Pro R9700 32GB ×2 138 tok/s decode · 3348 tok/s prefill

Showing 12 of 17 recipes on this page — filter or paginate for the rest.