I Tested Every Gemma 4 Model on a GTX 1650. Here's What Actually Happened.

This is a submission for the Gemma 4 Challenge: Write About Gemma 4 TL;DR: E4B is the model most developers should run locally. Here's why — tested on a GTX 1650 with real tasks, real numbers, and one bug it found that I didn't ask it to find. A GTX 1650 is not an impressive GPU. 4GB of VRAM. A card that benchmarking sites politely describe as "entry-level." It's the kind of hardware that AI demos don't mention — because most AI demos are built for A100s or at least an RTX 4090. I mention this upfront because it's the whole point of this post. I ran Gemma 4 — two variants of it — on that GTX 1650. I gave it real tasks: a document to analyze, a bug to fix, a photo of handwritten notes to read. And somewhere between watching it handle a coding problem better than I'd planned to, and seeing it transcribe messy handwriting from a photo with no internet connection, I realized the story here isn't about benchmarks. It's about who gets to build with capable AI now.