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Runpod Blog.

New Runpod datacenter now live: AP-IN-1 Track GPU spend across your team with Cost Centers The GPU supply supercycle is here. Here’s what AI builders need to know. Community Spotlight: One-click AI image and video generation on Runpod with SwarmUI | Runpod Blog Community Spotlight: LoRA Pilot Data Prep to Inference Introducing the Runpod Assistant: Manage Your Cloud GPU Resources with Natural Language OpenAI's Parameter Golf: Train the Best Language Model That Fits in 16MB on Runpod LLM inference optimization: techniques that actually reduce latency and cost Pruna P-Video and Vidu Q3 public endpoints now available on Runpod Runpod brand spelling guide Quickstart - Runpod Documentation The AI market looks nothing like the narrative Training StyleGAN3 with Vision-Aided GAN on Runpod KoboldAI – The Other Roleplay Front End, And Why You May Want to Use It How to Connect Cursor to LLM Pods on Runpod for Seamless AI Dev Community Spotlight: How AnonAI Scaled Its Private Chatbot Platform with Runpod Prompt Scheduling with Disco Diffusion on Runpod Runpod's Latest Innovation: Dockerless CLI for Streamlined AI Development Run Your Own AI from Your iPhone Using Runpod Introducing Flash: Run GPU workloads on Runpod Serverless: No Docker required Use Claude Code with your own model on Runpod: No Anthropic account required Avoid Errors by Selecting the Proper Resources for Your Pod What hackers built on Runpod at TreeHacks 2026 Easily Back Up and Restore Your Pod with Cloud Sync + Backblaze B2 The Complete Guide to GPU Requirements for LLM Fine-Tuning AI Guides, Tutorials & GPU Infrastructure Insights | Runpod Your first Claude Code project within Runpod: a complete setup guide 10 billion Serverless requests and counting Building for resilience: Runpod’s response to the AWS us-east-1 outage How to Connect Google Colab to Runpod Founder Series #1: The Runpod Origin Story AMD MI300X vs. NVIDIA H100: Mixtral 8x7B Inference Benchmark How to Run the FLUX Image Generator with ComfyUI on Runpod Run Llama 3.1 405B with Ollama on Runpod: Step-by-Step Deployment How to Run FLUX Image Generator with Runpod (No Coding Needed) How to Use 65B+ Language Models on Runpod Deploy Llama 3.1 with vLLM on Runpod Serverless: Fast, Scalable Inference in Minutes Open Source Video & LLM Roundup: The Best of What’s New Run vLLM on Runpod Serverless: Deploy Open Source LLMs in Minutes Introduction to vLLM and PagedAttention New update to Github integration: release rollback! | Runpod Blog A note to the developers who built Runpod with us Deploy ComfyUI as a Serverless API Endpoint Setting up Slurm on Runpod Clusters: A Technical Guide Building an OCR System Using Runpod Serverless From No-Code to Pro: Optimizing Mistral-7B on Runpod for Power Users Lessons While Using Generative Language and Audio For Practical Use Cases Runpod RoundUp 3 – AI Music and Stock Sound Effect Creation New Navigational Changes To Runpod UI Use alpha_value To Blast Through Context Limits in LLaMa-2 Models Runpod Roundup 5 – Visual/Language Comprehension, Code-Focused LLMs, and Bias Detection Runpod is Proud to Sponsor the StockDory Chess Engine Runpod Roundup 4 – Open Source LLM Evaluators, 3D Scene Reconstruction, Vector Search Meta and Microsoft Release Llama 2 as Open Source SuperHot 8k Token Context Models Are Here For Text Generation How to Manage Funding Your Runpod Account Encrypted Volumes on Runpod: Protect Your Data at Rest How to Run a "Hello World" on Runpod Serverless Runpod AI field notes: December 2025 Faster GitHub Builds: Major Performance Improvements to Our Automated Integration Partnering with Defined AI to Bridge the Data Wealth Gap How to Run Serverless AI and ML Workloads on Runpod How to fine-tune a model using Axolotl Transcribe and translate audio files with Faster Whisper Runpod Achieves SOC 2 Type II Certification: Continuing Our Compliance Journey Orchestrating GPU workloads on Runpod with dstack Exploring Runpod Serverless: Create Workers From Templates DeepSeek V3.1: A Technical Analysis of Key Changes from V3-0324 Deep Cogito Releases Suite of LLMs Trained with Iterative Policy Improvement Wan 2.2 Releases With a Plethora Of New Features Iterative Refinement Chains with Small Language Models The New Runpod.io: Clearer, Faster, Built for What’s Next Introducing Clusters: On-Demand Multi-Node AI Compute Run DeepSeek R1 on Just 480GB of VRAM How Do I Transfer Data Into My Runpod? 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InvokeAI Stable Diffusion on Runpod: Easy GPU Setup
Zhen Lu · 2022-12-07 · via Runpod Blog.

InvokeAI is a web-based creative engine for Stable Diffusion models used to generate, refine, and build visual AI workflows. This guide shows how to launch InvokeAI on Runpod when you want GPU-backed image generation without setting up CUDA and model dependencies locally.

Ever wanted to try invoke ai's awesome stable diffusion infinite canvas out, but didn't want to go through the hassle of installing a bunch of stuff? Maybe you just don't have a local GPU that can run it fast enough? No worries, we've got you covered with our easy deploy template for invoke ai!

If you don't have a powerful Nvidia GPU at home or you just don't want to go through the hassle of installing a bunch of drivers and managing dependencies, here's a really easy way to get started with invoke ai!

Just make sure to go to https://www.runpod.io/ and sign up for an account. Load up as little as $10 to get started.

I would recommend picking a 3090 GPU for this.

You can configure other settings to your liking, like requesting more disk space, or you can leave everything else default!

Deploy your instance through the UI, or you can click here to automatically load the template.

Runpod deploy step for 1x RTX A5000 with the fast Stable Diffusion image and a pricing summary

Go to your "My Pods" dashboard.

The new Invoke AI template does take a bit longer to set up, so this could take a few minutes or more depending on your pod's internet connection and CPU speed; please be patient! The older one started faster, but was harder to keep up to date with the latest features.

docker pull in InvokeAI Stable Diffusion on Runpod: Easy GPU Setup

You will know when your pod is ready when the CPU Utilization drops to 0%. This may take a minute or two.

After a few minutes, you can click Connect and then connect to jupyter lab:

Runpod connection options dialog with a Connect to Jupyter Lab on port 8888 button

Once you're in jupyter, start a terminal tab:

terminal JupyterLab in InvokeAI Stable Diffusion on Runpod: Easy GPU Setup

Then type invokeai-configure in your terminal window:

invoke launch in InvokeAI Stable Diffusion on Runpod: Easy GPU Setup

You should be presented with a menu of configuration options. Go through the menu options and make your choices to customize your invokeai experience.

invoke configure in InvokeAI Stable Diffusion on Runpod: Easy GPU Setup

Once this is complete, you should be able to launch the invoke UI by typing invokeai --web --host 0.0.0.0

in a terminal window.

invoke finished in InvokeAI Stable Diffusion on Runpod: Easy GPU Setup

Go back to your pod dashboard, where you can now connect via port 9090

invoke connect in InvokeAI Stable Diffusion on Runpod: Easy GPU Setup

You should then be directed to the invoke ai starting page

invoke ai started in InvokeAI Stable Diffusion on Runpod: Easy GPU Setup

Here are some cool videos made by the Invoke team showcasing their UI!

If you have any questions, or would just like to join the Runpod community, please visit us in Discord.

Author profile: Zhen Lu