Alibaba’s Qwen3 is here—with major performance improvements and a full range of models from 0.5B to 72B parameters. This post breaks down what’s new, how it compares to other open models, and what it means for developers.

Different stages of AI development call for different infrastructure. This post breaks down when GPU clusters shine—and how to scale up only when it counts.

Discover how Krnl transitioned from AWS to Runpod’s Serverless GPUs to support millions of users—slashing idle cost and scaling more efficiently.

MoE models scale efficiently by activating only a subset of parameters. Learn how this architecture works, why it’s gaining traction, and how Runpod supports MoE training and inference.

RunPod’s global networking feature is now available in 14 new data centers, improving latency and accessibility across North America, Europe, and Asia.

Learn how to fine-tune large language models using Axolotl on RunPod. This guide covers LoRA, 8-bit quantization, DeepSpeed, and GPU infrastructure setup.

See how the NVIDIA RTX 5090 stacks up in large language model benchmarks. We explore real-world performance and whether it’s the top GPU for AI workloads today.