Simon Willison’s Weblog

Introducing EmbeddingGemma. Brand new open weights (under the slightly janky Gemma license) 308M parameter embedding model from Google:

Based on the Gemma 3 architecture, EmbeddingGemma is trained on 100+ languages and is small enough to run on less than 200MB of RAM with quantization.

It's available via sentence-transformers, llama.cpp, MLX, Ollama, LMStudio and more.

As usual for these smaller models there's a Transformers.js demo (via) that runs directly in the browser (in Chrome variants) - Semantic Galaxy loads a ~400MB model and then lets you run embeddings against hundreds of text sentences, map them in a 2D space and run similarity searches to zoom to points within that space.