Google released the Gemma 4 family of open-weight AI models this week, ranging from a 2.3B-parameter E2B model up to a 31B dense model, with the smallest variants designed to run on-device. The E2B an…
Google released new Gemma 4 checkpoints optimized with Quantization-Aware Training (QAT) to reduce model memory footprint for local deployment on edge devices and consumer GPUs. The QAT process minimi…
Google DeepMind product managers Olivier Lacombe and Gus Martins announced Gemma 4 12B, a mid-sized open model under Apache 2.0 that runs multimodal and agentic tasks locally on laptops. The model bri…
The article explains that Google DeepMind's Gemma 4 model family, released on April 2, 2026, includes four variants (E2B, E4B, 26B A4B MoE, and 31B) designed for different deployment needs. It advises…
On April 2, 2026, Google DeepMind released Gemma 4, a family of open-weight AI models built from Gemini 3 research and available under a permissive Apache 2.0 license. The models are natively multimod…
A self-taught 19-year-old developer in Nigeria tested Google DeepMind's Gemma 4 E2B model on an 8GB RAM laptop without a GPU. He fed the model a degraded, double-compressed WhatsApp screenshot of code…