Ollama Embeddings
Local embedding generation through Ollama supporting models like nomic-embed-text and mxbai-embed-large. Enables completely offline embeddings with no subscription fees or API costs, ideal for privacy-focused RAG applications.
About this tool
Overview
Ollama provides local embedding generation capabilities, allowing you to run powerful embedding models completely offline on your computer. It's the recommended choice for building RAG applications locally with privacy.
Supported Embedding Models
- nomic-embed-text: Large context length encoder surpassing OpenAI ada-002
- nomic-embed-text-v2-moe: Multilingual MoE text embedding model
- mxbai-embed-large: High-performance embedding model
- all-minilm: Efficient sentence transformer model
Why Use Ollama for Embeddings
- Completely Free: No subscription fees or hidden costs
- Offline Capable: No internet connection required
- Privacy: Data never leaves your machine
- Efficient: Specialized models with smaller dimensions (1024 vs 4096 for LLMs)
- Simple API: Easy integration with localhost endpoint
Usage
Default API endpoint at http://localhost:11434/api/embeddings with simple curl interface for generating embeddings.
Integration
If you want to generate embeddings locally, Ollama with nomic-embed-text is the recommended approach. Widely supported across ChromaDB, LangChain, LlamaIndex, Haystack, and other RAG frameworks.
Use Cases
- Local RAG applications
- Privacy-sensitive document processing
- Offline AI applications
- Development and testing without API costs
- Air-gapped environments
Pricing
Completely free and open-source. No usage limits or API fees.
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