How to Run Google's Gemma 4 Locally with Ollama — All 4 Model Sizes Compared

Google dropped Gemma 4 two days ago and it's already everywhere — 1,700+ points on Hacker News, 80K+ downloads on HuggingFace. The benchmarks are genuinely insane: the E4B model (4.5B active parameters) beats Gemma 3 27B across the board. Math scores jumped from 20% to 89%. Agentic tasks from 6% to 86%. I've been building a local AI desktop app (Locally Uncensored) and added Gemma 4 support on day one. Here's a quick guide to running it locally with Ollama, plus what I've learned about the different model sizes. Install Gemma 4 with Ollama If you have Ollama installed, it's one command: # Default (E4B - best bang for buck) ollama run gemma4 # All available variants ollama run gemma4:e2b # 2.3B effective, 7.2 GB download ollama run gemma4:e4b # 4.5B effective, 9.6 GB download ollama run gemma4:26b # 3.8B active (MoE, 128 experts), 18 GB download ollama run gemma4:31b # 30.7B dense, 20 GB download All models support 128K-256K context, vision (image input), and native function calling. Wh