@jess @ben Just days ago, Google DeepMind launched Gemma 4 , a family of open models that signals a genuine shift in the AI landscape. Built from the same foundational research as the powerful Gemini 3, Gemma 4 brings frontier-level intelligence to your own hardware — no subscriptions, no API fees, just raw open-weight power. This guide breaks down everything you need to know: the four core variants, where each one shines, how to get started, and the groundbreaking capabilities that set Gemma 4 apart. Why Gemma 4 Matters: Performance Meets Open Access To understand the significance of this release, you need to look at the benchmarks. Across the board, the 31B dense model demonstrates a staggering performance leap over its predecessor, Gemma 3: AIME 2026 (Math Reasoning): 89.2% vs 20.8% LiveCodeBench v6 (Coding): 80.0% vs 29.1% GPQA Diamond (Scientific Knowledge): 84.3% vs 42.4% τ2-bench (Agentic Workflows): 86.4% vs 6.6% This performance is even more impressive considering its size.…