EmbeddingGemma 2 is a multimodal embedding model from Google built on the Gemma 4 architecture.
EmbeddingGemma is a 300M parameter embedding model from Google.
The IBM Granite Embedding 30M and 278M models models are text-only dense biencoder embedding models, with 30M available in English only and 278M serving multilingual use cases.
Turkish-first multimodal embeddings (text, images, audio) from Magibu AI, built on EmbeddingGemma 2: 768-d vectors, 8K context.
Jarvis Voice’s pinned EmbeddingGemma 300M BF16 artifact: 768-dimensional multilingual embeddings using one immutable model across cloud and local Ollama deployments.
EmbeddingGemma-300M-LawVault is a high-performance embedding model fine-tuned specifically for Chinese Legal RAG (Retrieval-Augmented Generation) scenarios.
Embedding Model embeddinggemma-300M-NVFP4-Q8-GGUF
This model is a GGUF version of embedding model which exists in this huggingface repository: https://huggingface.co/heydariAI/persian-embeddings
General Text Embeddings (GTE) model. Towards General Text Embeddings with Multi-stage Contrastive Learning trained by Alibaba DAMO Academy.
https://huggingface.co/bartowski/granite-embedding-278m-multilingual-GGUF