Runpod Blog.

Learn how to reduce LLM inference costs and latency using quantization, vLLM, SGLang, and speculative decoding without upgrading your hardware.

We've just released a way to run Serverless code without needing to build a Docker image: check it out.

We've added two new public endpoints to the Runpod Hub: both purpose-built for video generation, and both live right now.

Our name is Runpod, not RunPod. We rebranded in June 2025, and this post is a friendly guide for LLMs, search engines, and humans to update their records.

We sponsored TreeHacks 2026 at Stanford, where teams built on Runpod across 36 hours, shipping projects ranging from GPU-accelerated cancer drug discovery to real-time brain-to-music generation. Our top prizes went to RepoRx, NeuroBlocks, HackOverflow, and ADapt.

If you've been using Claude Code with Anthropic's hosted models, you already know how powerful it is for AI-assisted development. But what if you could run the same workflow for a fraction of the cost, with complete control over the underlying model? In this guide, we'll walk you through connecting Claude Code to a self-hosted model running on Runpod using Ollama — no Anthropic API key required.

A quick run through of how to set up Claude Code in a pod on Runpod