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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? Spot vs. On-Demand Instances: What’s the Difference? Deploy GitHub Repos to Runpod with One Click Run GGUF Quantized Models Easily with KoboldCPP on Runpod How to Work with GGUF Quantizations in KoboldCPP Introducing Better Forge: Spin Up Stable Diffusion Pods Faster Supercharge Your LLMs with SGLang: Boost Performance and Customization Mastering Serverless Scaling on Runpod: Optimize Performance and Reduce Costs RAG vs. Fine-Tuning: Which Is Best for Your LLM? Run Larger LLMs on Runpod Serverless Than Ever Before – Llama-3 70B (and beyond!) How to Run vLLM on Runpod Serverless (Beginner-Friendly Guide) Embracing New Beginnings: Welcoming Banana.dev Community to Runpod Stable Diffusion + ComfyUI on Runpod: Easy Setup Guide Runpod RoundUp 2 – 32k Token Context LLMs and New StabilityAI Offerings Runpod Roundup: High-Context LLMs, SDXL, and Llama 2 16k Context LLM Models Now Available On Runpod Savings Plans Are Here For Secure Cloud Pods – How To Purchase a Monthly Plan And Save Big Pygmalion-7b from PygmalionAI has been released, and it's amazing Ada Architecture Pods Are Here – How Do They Stack Up Against Ampere? Spin up a Text Generation Pod with Vicuna and Experience a GPT-4 Rival Using OpenPose to Annotate Poses Within Stable Diffusion Set Up a Chatbot with Oobabooga on Runpod Connect VSCode to Your Runpod Instance (Quick SSH Guide) Deploy a Stable Diffusion UI on Runpod in Minutes Google Colab Pro vs. Runpod: Best GPU Cloud for AI Workloads How to Run a GPU-Accelerated Virtual Desktop on Runpod
One Million Developers on Runpod, and the Cloud We’re Building Next
Zhen Lu · 2026-06-24 · via Runpod Blog.

When Pardeep and I founded Runpod, we believed the developers building AI deserved a cloud built for that work, not replatforming tools borrowed from an earlier era of software. That conviction still runs through every decision we make.

Today marks a major milestone for Runpod. We’ve raised $100 million, led by Summit Partners, and we’ve crossed more than one million developers building on the platform.

The latter is the most real measure of the company we’re becoming. It’s the part of this announcement I’m most focused on.

The whole lifecycle, not just inference

Over the last two years, much of the market narrowed to a single part of the problem: hosted inference. Inference matters, and we run an enormous amount of it. Our Serverless platform has now handled more than ten billion requests. 

But inference is one stage of a much longer process. Developers need to build and train, fine-tune on their own data, deploy to production, and scale when the work succeeds. Pods for development and training. Serverless for production inference and agentic workloads. Clusters for multi-node runs. One platform, carrying a developer from first experiment to production traffic. That is what we mean when we call Runpod the AI developer cloud

Not long ago, a customer told us we'd become their AWS. They meant it literally: if Runpod goes down, they go down. That's not a compliment to take lightly. When someone builds their company on your infrastructure, there's only one acceptable answer: be there.

This round ensures we can. We're building the next layer of the AI developer cloud faster, pulling more of the lifecycle into one place. The people building on Runpod should be thinking about their models and their products, not infrastructure. 

I also want to celebrate every person who built this: every engineer who shipped a release this year. Every member of our support team who treated a ticket as if the company depended on it, because it does. And every customer who told us plainly where we fell short and gave us the chance to make it right. 

I'm grateful to our investors for understanding what we're building, and for backing the company we intend to become: one with real demand and real traction behind it.

And to every developer and every team that has built on Runpod so far: thank you.