AI engineering glossary · NLP embeddings
What is MTEB (Massive Text Embedding Benchmark)?
Massive Text Embedding Benchmark (also called MTEB): A benchmark that evaluates text embedding models across many task types, such as retrieval, classification, clustering and similarity, in many datasets and some languages. It is widely used to compare embedding models and choose one for a job.
Massive Text Embedding Benchmark: an example
A team compares two embedding models by their MTEB retrieval scores before picking one for a document search feature.
Related terms
More NLP embeddings terms
- Matryoshka representation learning
- Mean pooling
- Morphology
- Multilingual embedding
- N-gram
- N-gram language model
- Named entity
- Named entity recognition
Where you learn it
Massive Text Embedding Benchmark is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.