How developers build AI for good with Gemma 4

Making the most of AI models requires brilliant engineering. That's why today we're excited to announce the winners of the Gemma 4 Good Challenge, a Kaggle competition that asked participants to bring impactful AI solutions to the world.

While Gemma 4 models allow developers to innovate without limits, deploying them in resource-constrained environments represents a technical challenge. Developers used key technologies, including LiteRT, Cactus, Ollama, llama.cpp, and Unsloth, to create highly performant solutions for everyday hardware. Here are the winners:

First Place

GEM-4 is a physical robotic assistant and control pipeline built to physically assist elderly and disabled individuals with daily living tasks. Using a Gemma 4 31B model to label video training clips, a fine-tuned, lightweight Gemma 4 E2B controller translates visual observations and language instructions into real-world physical movements. Judges lauded GEM-4 for its innovative closed-loop data engine and Vision-Language-Action (VLA) architecture, creating an embodied system that moves AI reasoning directly into hands-on physical help.