Google Releases EmbeddingGemma 2: 740M Open Multimodal Embedding Model Running on 0.5GB RAM
gnukeith · x · 2026-10-07
Google DeepMind released EmbeddingGemma 2, its first natively multimodal open embedding model for on-device use: 740M total parameters (270M text + 170M vision + 300M audio) under Apache 2.0, unifying code, images, audio, and video in a shared 768-dimensional space across 100+ languages, runnable locally on 0.5GB of RAM. Unsloth provides GGUF quants and a training guide; the model card includes 768d benchmark results with and without vector truncation.
Related event: Google releases open-source multimodal EmbeddingGemma 2(27 posts)→
More from Models
- Google's multimodal embeddinggemma-2 trends on Hugging Face — google · 2026-10-07
- Mistral CEO: Large 4 trained on our own compute, 'RL shows no sign of saturation' — sivareddyg · 2026-10-07
- Tesla's Grok voice goes hoarse but can't hear itself — a look at AI engineering shortcuts — PTrubey · 2026-10-07
- Perplexity ships open-weights pplx-decider-v1.1-27b at half the cost of v1 — perplexity_ai · 2026-10-07
- Mistral launches Large 4: 1T-param multimodal model, 49B active, open weights in October — beffjezos · 2026-10-07
- Perplexity's open-weights pplx-decider-v1.1-27b tops Hugging Face Decision Index 0.3 — AravSrinivas · 2026-10-07