🧮 Embeddings
Embedding models for search, similarity, and RAG. 10 models.
Cohere: Embed 4
Embed 4 is Cohere's most performant multilingual multimodal embedding model. It transforms different modalities such as images, texts, and interleaved images and texts into a single vector representat...
Google AI: Gemini Embedding
Gemini Embedding is a text embedding model for semantic search and vector-based tasks. Developed by Google AI, this model is optimized for its specific use case category.
Google: Gecko Embedding
Lightweight embedding model.
Google: Gemini Text Embedding 004
Latest text embedding model.
Mistral AI: Codestral Embed
Codestral Embed is a text embedding model for semantic search and vector-based tasks. Developed by Mistral AI, this model is optimized for its specific use case category.
Mistral AI: Mistral Embed
Mistral Embed is a text embedding model for semantic search and vector-based tasks. Developed by Mistral AI, this model is optimized for its specific use case category.
Ollama: Embeddinggemma:300m
Embeddinggemma:300m optimized for generating high-quality embeddings. This model supports multimodal capabilities including vision and image understanding.
OpenAI: Text Embedding 3 Large
Large embedding model for advanced semantic tasks. This model supports multimodal capabilities including vision and image understanding. It features advanced reasoning capabilities for complex problem...
OpenAI: Text Embedding 3 Small
Efficient text embedding model with high quality representations. This model supports multimodal capabilities including vision and image understanding. It features advanced reasoning capabilities for ...
OpenAI: Text Embedding Ada 002
Legacy embedding model still widely used. This model supports multimodal capabilities including vision and image understanding. It features advanced reasoning capabilities for complex problem-solving ...