Thenlper
Thenlper: GTE-Base
thenlper/gte-base
The gte-base embedding model encodes English sentences and paragraphs into a 768-dimensional dense vector space, delivering efficient and effective semantic embeddings optimized for textual similarity, semantic search, and clustering applications.
Input
$0.005
/ 1M tokens · Token reference
Output
$0
/ 1M tokens · Token reference
Context window
512
tokens
Embeddings output · Token reference fields do not establish an output-unit price.
Limits
Context
512
tokens
Max output
460
90% of the context window
Parameters
109,482,752
Model facts
Author
Thenlper
Tokenizer
Other
Modality
Text -> Embeddings
License
MIT
Created
Nov 18, 2025
Hugging Face
thenlper/gte-base
Publication status
Hugging Face: verifiedLicense: publishedParameter count: published
Modalities
Input · TextOutput · Embeddings