
Deploy Embedding Gemma
Generate high-quality text embeddings with Google's best model
Embedding Gemma
ollama/ollama
Just deployed
/root/.ollama
Auth Proxy
FraglyG/CaddyAuthProxy
Just deployed
Deploy and Host EmbeddingGemma AI on Railway
EmbeddingGemma is Google's state-of-the-art embedding model that generates vector representations of text for search and retrieval tasks. With just 308M parameters, it achieves #1 ranking on the MTEB leaderboard among models under 500M parameters, making it perfect for privacy-focused, on-device applications that require high-quality embeddings.
About Hosting EmbeddingGemma
Hosting EmbeddingGemma provides access to the highest-ranking open multilingual text embedding model under 500M parameters, trained on 100+ languages and optimized to run on less than 200MB of RAM with quantization. This deployment handles vector embedding generation, multilingual text processing, and semantic similarity computations. With sub-15ms inference latency for 256 tokens, it's ideal for real-time applications requiring fast, accurate text embeddings without sending data to external services.
Common Use Cases
- Semantic Search Systems: Build powerful search engines that understand meaning rather than just keywords
- Document Classification: Automatically categorize and organize text content across multiple languages
- Recommendation Engines: Create content recommendation systems based on semantic similarity
- RAG Applications: Power retrieval-augmented generation systems with high-quality embeddings
- Clustering and Analytics: Group similar documents and perform advanced text analytics
- Privacy-First AI: Run embedding generation on your own infrastructure without data leaving your environment
Dependencies for EmbeddingGemma Hosting
- Ollama Runtime: Serves the EmbeddingGemma model through standardized API endpoints
- Authentication Proxy: Secures access to your embedding generation service
- Vector Processing: Handles high-dimensional embedding computations and similarity calculations
Deployment Dependencies
- EmbeddingGemma Model Documentation
- Ollama EmbeddingGemma Model
- MTEB Benchmark Results
- Railway Deployment Guide
Implementation Details
This template is a distro of the Ollama API template but comes pre-configured with EmbeddingGemma.
Usage example:
POST /api/embeddings
Headers:
Authorization: Bearer your-api-key
Content-Type: application/json
Body: {
"model": "embeddinggemma:300m",
"prompt": "Your text to embed"
}
The model uses bi-directional attention architecture, effectively functioning as an encoder optimized specifically for embedding generation rather than text completion.
Why Deploy EmbeddingGemma on Railway?
Railway is a singular platform to deploy your infrastructure stack. Railway will host your infrastructure so you don't have to deal with configuration, while allowing you to vertically and horizontally scale it.
By deploying EmbeddingGemma on Railway, you are one step closer to supporting a complete full-stack application with minimal burden. Host your servers, databases, AI agents, and more on Railway.
Template Content
Embedding Gemma
ollama/ollamaAuth Proxy
FraglyG/CaddyAuthProxyAPI_KEY