- Input
- $0.005
- Output
- $0.00
BAAIListed Nov 22, 2023
bge-base-en-v1.5
BGE embedding is a general Embedding Model. It is pre-trained using retromae and trained on large-scale pair data using contrastive learning. Note that the goal of pre-training is to reconstruct the text, and the pre-trained model cannot be used for similarity calculation directly, it needs to be fine-tuned
Measured performance
All leaderboards ↗Benchmark results
No published results in this index yet
Scores appear here when an evaluation matches this exact model.
Access & cost
1 quotePrices across providers
Model specifications
- Developer
- BAAI
- Modality
- Embedding
- Context
- 512 tokens
- Maximum output
- 460 tokens
- Weights
- Open weights
- Provider listed
- Nov 22, 2023
- First discovered
- Oct 16, 2026
Exact identities
- openrouter
baai/bge-base-en-v1.5 - deepinfra
BAAI/bge-base-en-v1.5
Sources
Updated Oct 17, 2026
More from BAAI
View all ↗BAAIListed Sep 3
bge-m3-multi-8k
BGE-M3 is a multilingual text embedding model developed by BAAI, distinguished by its Multi-Linguality (supporting 100+ languages), Multi-Functionality (unified dense, multi-vector, and sparse retrieval),…
8.2K contextNo reported score
No reported score
Price not listed
BAAIListed Feb 28
bge-m3-multi
BGE-M3 is a multilingual text embedding model developed by BAAI, distinguished by its Multi-Linguality (supporting 100+ languages), Multi-Functionality (unified dense, multi-vector, and sparse retrieval),…
512 contextNo reported score
No reported score
Price not listed
BAAIListed Jan 31
bge-en-icl
A LLM-based embedding model with in-context learning capabilities that achieves SOTA performance on BEIR and AIR-Bench. It leverages few-shot examples to enhance task performance.
8.2K contextNo reported score
No reported score
Price not listed
BAAIListed May 27
bge-m3
BGE-M3 is a versatile text embedding model that supports multi-functionality, multi-linguality, and multi-granularity, allowing it to perform dense retrieval, multi-vector retrieval, and sparse retrieval in…
8.2K contextOpen weightsNo reported score
No reported score