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 PRO 6000 Blackwell 96GB: Any4 cards (5)3 cards (1)2 cards (5)1 card (7)DGX Spark 128GB (Blackwell): Any4 cards (3)3 cards (1)2 cards (3)1 card (10)RTX 5090 32GB (Blackwell): Any2 cards (1)1 card (1)
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9 recipes · page 1 of 1

Blackwell (1)

Community builds

Blackwell (7)

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
Qwen3.8-Flash-Next NVFP4 1x DGX Spark vLLM 71.3 c1 (salient-data)

by Jeremy Newhouse / salient-data (recipe, patches, measurements)↗, tonyd2wild (bench_categories.py @ 6ad1c8f + comparator stack/numbers)↗, NVIDIA (Qwen3.8-Flash-Next-NVFP4 checkpoint; HF token gated)↗, vLLM project (nightly base image 8e2beaa3)↗, Sigstore/cosign (image signing + SBOM timestamping)↗ · listed by localai-recipes

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

Qwen3.8-Flash-Next TP vllm +2

Ampere (1)

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

Qwen3.8-Flash-Next 3bpw FP8-PLE 1x CMP 170HX DFlash2 RecoverSSM

by ElectroHobo↗, Morrowmake (vllm-cmp170hx engine + image + Qwen EXL3 recipe scripts this descends from, MIT)↗, klee100 (3 bpw AutoRound checkpoint with its MTP head, made for a 64 GiB card; not involved in this recipe)↗, halt95 (W4A16-Merlin checkpoint whose FP8 n-gram table this recipe serves; not involved in this recipe)↗, inco.ai (DFlash2 drafter, Apache-2.0)↗, Intel (AutoRound quantisation) + RadixArk (FP8 n-gram table quantisation)↗, Qwen (Qwen3.8-Flash-Next base model, Qwen Community License 1.0)↗, MiaAI-Lab (benchmark protocol + category prompts, used as data)↗ · listed by localai-recipes

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

Qwen3.8-Flash-Next TP vllm +2