BGE M3
Specifications
- Input
- Output
- Context window
- 8K tokens
- Veröffentlicht
- Jan 2024
Performance
- Speed
- 2121 t/s
- TTFT
- —
- Latency
- 1.4s
- Intelligence
- —
Pricing
- Eingabe
- €0.01 per 1M tokens
- Ausgabe
- €0.00 per 1M tokens
Über dieses Modell
BAAI BGE-M3 is a versatile multilingual embedding model supporting dense, sparse, and multi-vector retrieval in a unified architecture. Handles 100+ languages with strong cross-lingual capabilities and flexible retrieval modes for different use cases. Features hybrid retrieval combining dense embeddings for semantic similarity, sparse representations for lexical matching, and multi-vector approaches for fine-grained relevance. Ideal for multilingual search engines, hybrid retrieval systems, and complex information retrieval scenarios requiring multiple matching strategies.
Technische Daten
- Fähigkeiten
- Eingabe-Modalitäten
- Ausgabe-Modalitäten
- Reasoning
- No
Knowledge horizon
Veröffentlicht Jan 2024
Today
Since release 29 mo
See also
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