Alibaba-NLP/gte-modernbert-base
Primitive: /encode · Encode ·
ModernBERT
We are excited to introduce the `gte-modernbert` series of models, which are built upon the latest modernBERT pre-trained encoder-only foundation models. The `gte-modernbert` series models include both text embedding models and rerank models.
View on Hugging Face → Fine-tuned from answerdotai/ModernBERT-base
Overview
Hardware: — drives latency, throughput & cost
| Size | 149M params |
|---|---|
| Tasks | /encode |
| License | apache-2.0 |
| Languages | en |
| Latency | — |
| Throughput | — |
| Cost | — /1M tok |
Cost is approximate — computed from list GPU prices; your actual price depends on the provider you deploy SIE with.
Embedding
| Output types | Dense |
|---|---|
| Dimensions | dense: 768 |
| Max sequence length | 8,192 |
| Inputs | text |
Benchmarks
CQADupstackPhysicsRetrieval
Duplicate question retrieval from StackExchange Physics
CosQA
Code search with natural language queries
FiQA2018
Financial opinion mining and question answering
NFCorpus
Biomedical literature search from NutritionFacts.org
SCIDOCS
Citation prediction, document classification, and recommendation for scientific papers
SciFact
Scientific claim verification using research literature
StackOverflowQA
Programming question answering from Stack Overflow