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Runpod Blog.

DeepSeek V4 in the wild, and how to run it on Runpod 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 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
Founder Series #1: The Runpod Origin Story
Pardeep Singh · 2026-02-18 · via Runpod Blog.

Founder Series #1: The Runpod Origin Story

Let's get more personal and establish a baseline. For everyone that's been enjoying Runpod, thank you for spreading the word. I am Pardeep Singh (aka flash-singh), CTO at Runpod and one of the co-founders along with Zhen Lu.

What triggered me to share?

Of all things non-engineering, I tend to put them off until... I had a conversation with one of our investors, Daniel Docter, over tequila shots on why our content isn't hitting the mark. He was obviously not impressed, and I don't blame him. To lead by example, I am starting Founder Series to shed more light on Runpod: how we came to be, what architecture decisions we have made, and why. What is my take on humanity and AI?

To my earlier point, let's get personal.

I am an engineer, have been since before college. For much of my time, I like to be heads down coding or deep in my thoughts, moving around the puzzle pieces. Needless to say, I enjoy solving problems and love the focus on MVP. Deliver small, think big. It's essential to learning and adapting fast.

How did I get wrapped in a startup?

Since my late high school days, I have been fascinated with coding. I spent the majority of my time coding and playing WoW during college. I paid for my college with a free music app focused on creating YouTube playlists before it was a thing. My journey has always been focused on creating something that people can experience and enjoy.

There was a time when I listened to many audiobooks for motivation and inspiration. That was a time after college; life drastically changed, and looking forward to a 9 to 5 isn't an easy transition. One of the quotes I heard really stuck with me, and every time I run into a road bump, I am reminded of it.

The graveyard is the richest place on earth, because it is here that you will find all the hopes and dreams that were never fulfilled, the books that were never written, the songs that were never sung, the inventions that were never shared, the cures that were never discovered, all because someone was too afraid to take that first step, keep with the problem, or determined to carry out their dream. - Les Brown

There are times when I imagine myself laying in my deathbed and regretting things I could have done or accomplished. That fear keeps me going, and the fear of failure doesn't faze me anymore. Talking about failures, let's jump to 2021, the year of my most failures.

What happened in 2021 other than COVID?

  1. Built a free workout app (learned Flutter; it was a joy)
    1. As far as business goes, my heart wasn't in it, and the market is very saturated; it was a good pastime since my wife loves working out, and every time I would show her all the small improvements I made.
    2. Lesson Learned: Do something you desire and make sure it's challenging.
  2. Started a jewelry business
    1. Thanks to my wife, who kept telling me it's easy, just buy from Alibaba and sell on Amazon; sunk $4k in.
    2. As a last resort, I went to a local flea market to sell and came home disappointed with 0 sales. Still have boxes of jewelry sitting in my basement.
    3. Lesson Learned: Be an engineer; fail fast.
  3. Zhen reached out wanting to mine crypto; sure, why not!
    1. Within a month, I scoured the depths of PA / NYC to scrape up any GPU I could find. Easily sunk $15k in; my wife was not happy about the time I spent running around more than the actual cost of it.
    2. ETH mining was coming to an end in early 2022 due to POS, and I started researching AI. Poured another $10k into hardware to upgrade my rigs to AI servers. For those not aware, mining rigs are built MVP-style with shortcuts to ROI ASAP.
    3. After a couple of months of experimenting with AI servers and dedicating my compute on various sites, I concluded the experience was mediocre. There was a 100% chance I could do it better, 0% chance I knew how to market it.
    4. Lesson Learned: Find opportunities in failures; explore the unknown.
  4. YOLO! Journey to GPU Cloud.
    1. First, I had to pitch the idea to my wife and make sure she was onboard. Of course, I wouldn't spend weekends working on this project.
    2. Then setup multiple date-nights with Zhen and his wife, he wasn't buying it at first but I was obsessed with the idea.
    3. On our way to the bank, he shared his interest in wanting to be the CEO. I didn't give it a second thought; for the most part I was never fond of bureaucracy and the politics of being a CEO.
    4. The months and years that followed changed our lives drastically.

The start of the Runpod journey.

Talk is cheap. We spent the next 3 months developing Runpod with the direction of a simple and fast GPU Cloud experience. By this point, I was already a Golang fan and that made things easier.

Challenge #1: How to connect distributed compute and isolate them from one another?
Challenge #2: How to securely connect services running in containers to users outside the local network? Another caveat was that none of these servers had static public IPs.

Tune in next time for more details on the Runpod MVP journey.

Author profile: Pardeep Singh

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