embeddinggemma-300m
EmbeddingGemma is a 300M parameter, state-of-the-art for its size, open embedding model from Google, built from Gemma 3 (with T5Gemma initialization) and the same research and technology used to create Gemini models. EmbeddingGemma produces vector representations of text, making it well-suited for search and retrieval tasks, including classification, clustering, and semantic similarity search. This model was trained with data in 100+ spoken languages.
- Context window
- — tokens
- Input cost
- $0.00 / 1M
- Output cost
- $0.00 / 1M
- Latency (p50)
- —