Embedding Models
AI models for text embeddings and semantic search
Embedding · Google
Model maker
All model series
1 seriesChoosing the right embedding model
The right model balances task fit, output quality, latency, and price.
Selection signals
- Match the model to the input and output you actually need.
- Compare models that use the same pricing unit.
- A small test reveals quality and latency differences that a catalog cannot.
FAQ
What makes a good embedding model?
A strong fit matches the task, quality bar, latency target, and budget. A small evaluation set makes quality and reliability differences easier to see.
Can I switch models later?
Yes. Keep the public model ID and request format explicit, and compare alternatives on the same tasks.