RunPod
RunPod Tutorial
RunPod is a cloud GPU provider that gives you affordable, on-demand access to powerful GPUs like NVIDIA A100s and H100s. It’s built for training and running AI models, Stable Diffusion, and custom LLMs without needing your own expensive hardware.
Make Money With This 💰
Sell Stable Diffusion image packs (built with RunPod templates).
Host API endpoints for custom AI services and charge clients.
Train fine-tuned models for small businesses.
Use Cases
AI Researchers → train large models without buying GPUs.
Artists → run Stable Diffusion at scale.
Startups → deploy AI apps cost-effectively.
Developers → create hosted APIs for clients.
Key Features
On-demand GPU rental
Wide range of GPU types (NVIDIA A100, H100, RTX 4090, etc.)
Pay-as-you-go or long-term spot instances
API for deployment automation
Pre-configured AI environments (PyTorch, TensorFlow, Stable Diffusion, etc.)
Shared & dedicated GPU options
Getting Started
Step 1: Go to RunPod and sign up for an account.
Step 2: Add payment method (credit card or PayPal).
Step 3: From the dashboard, choose Deploy → GPU Instance.
Step 4: Select GPU type (e.g., RTX 4090 for small AI projects, A100 for heavy training).
Step 5: Pick a template (Stable Diffusion, PyTorch, Jupyter Notebook, etc.).
Step 6: Click Deploy and wait for your pod (GPU instance) to spin up.
Step 7: Connect through Jupyter, SSH, or API.
Step 8: Your GPU pod is now ready for training, inference, or experiments.
Example Prompt
Type: “A futuristic cityscape at sunset, neon lights reflecting on skyscrapers, cinematic style”
What you’ll see: A generated image showing a cyberpunk-inspired futuristic skyline.
Tool Snapshot: Pros & Cautions
Best if: you need cheap GPU compute for AI training or inference.
Not ideal if: you prefer a fully no-code AI tool — RunPod still requires some setup.
Pricing Snapshot
Pay-as-you-go: starting ~$0.20/hour for RTX 3090.
On-demand A100: ~$1.50–$2.00/hour.
Spot pricing available for cheaper bursts.