Google just casually disrupted the open-source AI narrative…

Google released Gemma 4 under the Apache 2.0 license, making it truly free and open source — a rarity among major tech companies. What makes it stand out is its small size: the largest variant runs on a consumer RTX 4090 with a 20 GB download, while edge variants run on phones or Raspberry Pi, yet it benchmarks comparably to much larger models requiring data center hardware. The efficiency comes from two techniques: per-layer embeddings, which give each transformer layer its own token representation so information is introduced only when needed, and TurboQuant, a new quantization approach that converts weights to polar coordinates and uses the Johnson-Lindenstrauss transform to compress high-dimensional data to single sign bits while preserving distances. The result is a small, capable, locally-runnable model suitable for fine-tuning with tools like Unsloth.