Gemma

Releases

1. Oct 6

   EmbeddingGemma 2 · 0.74B · open weights

2. Jun 10

   DiffusionGemma · 26B · 3.8B active · open weights

3. Apr 2

   Gemma 4 · 26B / 31B · open weights

Trends

• Open-weight models diversify in architecture, modality, and size
• Western labs counter China's open-weight lead

Items

1. Oct 6

   Google DeepMind's EmbeddingGemma 2

   A 740M-parameter, Apache-2.0 multimodal embedding model on the Gemma 4 architecture that maps text, images, audio, video, and code into one space for on-device RAG and zero-shot routing, running the full model in ~567 MB of RAM.

2. Jun 10

   Google DeepMind's DiffusionGemma

   An experimental open 26B-A4B MoE (3.8B active) that generates text by discrete diffusion, emitting 256-token blocks in parallel with bidirectional attention, for up to 4-5x faster decoding (over 1,000 tokens/sec on one H100) under Apache 2.0.

3. Apr 2

   Google DeepMind's Gemma 4

   A four-size Apache-2.0 open family (E2B, E4B, 26B MoE, 31B Dense) built from Gemini 3 research, with native text, image, audio, and video input and up to 256K context; the 31B Dense ranks #3 on Arena AI, ahead of models up to 20x larger.