Runpod Blog.

GPUs still dominate AI training in 2025, but emerging hardware and hybrid infrastructure are reshaping what's possible. Here’s what GTC revealed—and what it means for you.

Meta’s Llama 4 models, Scout and Maverick, are the next evolution in open LLMs. This post explores their strengths, performance, and deployment on Runpod.

San Francisco-based Deep Cogito used RunPod infrastructure to train Cogito v1, a high-performance open model family aiming at artificial superintelligence. Here’s how they did it.

Curious but not technical? Here’s how I ran Mistral 7B on a cloud GPU using only no-code tools—plus what I learned as a complete beginner.

Runpod’s Instant Clusters let you spin up multi-node GPU environments instantly—ideal for scaling LLM training or distributed inference workloads without config files or contracts.

You don’t need to code to understand machine learning. This guide explains how AI models learn, and how to explore them without a technical background.

With the launch of AP-JP-1 in Fukushima, RunPod expands its Asia-Pacific footprint—improving latency, access, and compute availability across the region.