gemini-embedding-2 · Gemini · embedding
Gemini Embedding 2 is Google DeepMind's vectorization model. It supports text embedding vectorization, producing 768-dimensional vectors. Ideal for retrieval-augmented generation (RAG), semantic search, clustering, classification, and similar tasks. Compatible with both Vertex AI and the Gemini API.
Text vectorization (768 dimensions); multilingual support; semantic search; RAG retrieval; clustering analysis; classification tasks; Vertex AI compatible.
RAG (retrieval-augmented generation); semantic search; document clustering; classification tasks; recommendation systems; deduplication and similarity matching.
No text generation (vectors only); no vision understanding; no Function Calling support; fixed 768 output dimensions.
Anthropic official CLI coding agent. Multi-file edits, tool use, long-context reasoning.
export ANTHROPIC_AUTH_TOKEN="YOUR_API_KEY"
export ANTHROPIC_BASE_URL="https://api.robovai.com"
export ANTHROPIC_MODEL="gemini-embedding-2"
claude