Read latest product features, solutions, and updates.

Meta's renewed open-model push puts deployment control back in focus. Here is how to evaluate Gemma 4 without confusing open weights with effortless operations.

What Kubernetes taught infrastructure teams — and what the open-weight AI shift means for deploying, evaluating, and governing a local AI model.

A practical guide to choosing between Gemma 4 E2B, E4B, 12B, 26B A4B, and 31B Dense models based on your hardware, use case, and performance needs.

Learn how to run Gemma 4 on your local machine using Ollama, llama.cpp, LM Studio, and more — from mobile devices to workstations.

Everything you need to know about Gemma 4 — Google DeepMind's open-source multimodal AI model family with built-in reasoning, 256K context, and 140+ language support.