- Input
- $0.005
- Output
- $0.00
intfloatListed Nov 22, 2023
Intfloat: E5-Base-v2
The e5-base-v2 embedding model encodes English sentences and paragraphs into a 768-dimensional dense vector space, producing efficient and high-quality semantic embeddings optimized for tasks such as semantic search, similarity scoring,...
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
- intfloat
- 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
intfloat/e5-base-v2 - deepinfra
intfloat/e5-base-v2
Sources
Updated Oct 18, 2026
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The multilingual-e5-large embedding model encodes sentences, paragraphs, and documents across over 90 languages into a 1024-dimensional dense vector space, delivering robust semantic embeddings optimized…
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intfloatListed Nov 22
Intfloat: E5-Large-v2
The e5-large-v2 embedding model maps English sentences, paragraphs, and documents into a 1024-dimensional dense vector space, delivering high-accuracy semantic embeddings optimized for retrieval, semantic…
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