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Step-by-step guides for building and deploying example applications on Runpod.

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Serverless

For CPU-based inference, follow the Ollama Serverless tutorial.

Create an image generation endpoint

Deploy a Stable Diffusion endpoint and generate your first AI image.

Integrate with a web application

Deploy an image generation endpoint and integrate it into a web app.

Deploy a cached model

Serve an LLM with reduced cost and cold start times.

Deploy a chatbot with Gemma 3

Use vLLM and the OpenAI API to build an interactive chatbot.

Generate images with ComfyUI

Deploy ComfyUI and generate images using JSON workflows.

Run Ollama on Serverless CPU

Deploy an Ollama server on CPU workers and send an inference request.

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Flash

Generate images with Flash

Deploy SDXL as a serverless endpoint with Python decorators.

Text generation with Transformers

Deploy a text generation model on Runpod.

Build a load balancing API

Create a REST API with automatic load balancing.

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Pods

Run LLM inference with JupyterLab

Launch JupyterLab on a GPU Pod and run inference with Transformers.

Pods + Ollama

Deploy Ollama on a GPU Pod and run inference using the Ollama API.

Build Docker images with Bazel

Build Docker images on Pods using Bazel.

Generate images with ComfyUI

Deploy ComfyUI on a GPU Pod and use the web interface.

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Public Endpoints

Build a text-to-video pipeline

Chain multiple Public Endpoints to generate videos from text.

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More resources

Review container tutorials for packaging guidance, or browse community video resources for additional walkthroughs.

Container tutorials

Learn container fundamentals, Dockerfile creation, persistence, and common Docker commands.

Community video resources

Browse community tutorials about Runpod workflows and supporting Linux tools.
Last modified on September 2, 2026