noonghunna/club-3090 resource

Health v2 · maintenance only

Flags: young

Adoption not part of the score

2101 stars · 127 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A community-maintained collection of recipes, configs, and scripts for serving large language models locally on consumer NVIDIA GPUs (RTX 3090/4090/5090). It is multi-engine (vLLM, llama.cpp, ik_llama) and model-agnostic, shipping curated launch scripts, hardware-aware pickers, and benchmarks for single- and dual-GPU setups.

Use cases

• serve llms locally on rtx 3090
• run qwen or gemma on two consumer gpus
• find working vllm configs for 24gb cards
• self-host an llm backend in a homelab
• benchmark llama.cpp vs vllm on consumer gpus
• set up local llm with open webui and image generation

When to choose

• You own one or two RTX 3090/4090/5090 cards and want proven serving configs
• You want a scripted, hardware-aware setup for local LLM inference on Linux/macOS or WSL2
• You want curated per-model defaults with VRAM budgeting and benchmarks

When to avoid

• You need production multi-node or datacenter GPU serving
• You run native Windows without WSL2 (tooling is unsupported there)
• You need a general-purpose inference library rather than curated configs and scripts

Facets

infra-config · maturity active

llm-inference configuration-management deployment benchmarking developer-tools large-language-models self-hosted gpu-computing developer-tools hardware self-hosted cli consumer-gpus rtx-3090 rtx-4090 rtx-5090 vllm llama-cpp local-llm homelab model-serving recipes qwen gemma linux macos gpu docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="noonghunna/club-3090")