🖥️ Your Platform: Detecting...
Commands below auto-adjust for your operating system
🖼️ Image Generation Runtimes
Run FLUX, Stable Diffusion, and all LoRA models locally
ComfyUI
The most powerful node-based image generation GUI. Drag-and-drop workflows, supports every model format.
git clone https://github.com/comfyanonymous/ComfyUI && cd ComfyUI && pip install -r requirements.txt
Stable Diffusion WebUI (Auto1111)
Classic web interface for Stable Diffusion. Huge extension ecosystem, simple LoRA management.
git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui && cd stable-diffusion-webui && ./webui.sh
SD WebUI Forge
Optimized fork of Auto1111 — 30-60% faster, lower VRAM usage, FLUX support built-in.
git clone https://github.com/lllyasviel/stable-diffusion-webui-forge && cd stable-diffusion-webui-forge && ./webui.sh
Diffusers (Python)
HuggingFace's Python library — programmatic control, scripting, batch processing. Supports all models.
pip install diffusers transformers torch accelerate safetensors
InvokeAI
Professional creative AI tool — unified canvas, layer support, inpainting, outpainting.
pip install invokeai && invokeai-web
Draw Things
Native macOS/iOS app — optimized for Apple Silicon, Metal GPU acceleration.
Available on Mac App Store — FREE
🧠 LLM Runtimes (Text Generation)
Run large language models locally — chat, code, reasoning, all offline
Ollama
Simplest way to run LLMs locally. One command to download and run any model. Built-in API server.
curl -fsSL https://ollama.com/install.sh | sh && ollama pull llama3.1
vLLM
High-throughput LLM serving engine — fastest inference, PagedAttention, continuous batching.
pip install vllm && vllm serve meta-llama/Llama-3.1-8B-Instruct
llama.cpp
CPU/GPU inference for GGUF models — runs on ANY hardware, even without GPU.
git clone https://github.com/ggerganov/llama.cpp && cd llama.cpp && make -j
LM Studio
Beautiful desktop GUI — discover, download, and run LLMs with zero config. ChatGPT-like interface.
Download from lmstudio.ai — FREE for personal use
Jan
Open-source ChatGPT alternative — runs 100% offline, clean UI, plugin system.
Download from jan.ai — FREE & open source
MLX LM (Apple Silicon)
Apple's ML framework — optimized for M1/M2/M3 chips, unified memory for large models.
pip install mlx-lm && mlx_lm.generate --model mlx-community/Llama-3.1-8B-Instruct-4bit
🖥️ 100TB Server Setup Guide
Complete guide to set up your servers for the ultimate AI model library
Step 1: System Preparation
sudo apt update && sudo apt install -y git git-lfs python3 python3-pip nvidia-driver-535 nvidia-cuda-toolkit
git lfs install
Step 2: Create Model Storage
sudo mkdir -p /mnt/100tb/models/{foundation,loras,characters,editing,llms} && sudo chown -R $USER:$USER /mnt/100tb/models
Step 3: Install AI Runtimes
pip install torch torchvision diffusers transformers accelerate safetensors huggingface_hub vllm invokeai
curl -fsSL https://ollama.com/install.sh | sh
git clone https://github.com/comfyanonymous/ComfyUI /opt/comfyui && cd /opt/comfyui && pip install -r requirements.txt
Step 4: Download All Models (No Login!)
cd /mnt/100tb/models/foundation && git clone https://huggingface.co/black-forest-labs/FLUX.1-dev && git clone https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0
💡 Pro tip: Visit the AI Models Hub and click "Copy Bulk Script" to get ALL 60+ model download commands at once!
💻 Hardware Requirements
What you need for different model sizes
Entry Level
GPU: 8GB VRAM (RTX 3060/4060)
RAM: 16GB
Storage: 500GB SSD
✅ Runs: SDXL, small LoRAs, 7B LLMs, Ollama
Mid Range
GPU: 16-24GB VRAM (RTX 4080/4090)
RAM: 32-64GB
Storage: 2TB NVMe
✅ Runs: FLUX.1, SD3, all LoRAs, 30B LLMs
Power User / Server
GPU: 48-80GB VRAM (A100/H100)
RAM: 128GB+
Storage: 100TB (your setup!)
✅ Runs: EVERYTHING. All models, all sizes, concurrent serving.