BGE M3
by BAAI
Multi-lingual, multi-functionality, multi-granularity embedding model.
Quick Facts
- Model Size
- 568M
- Context Length
- N/A
- Release Date
- Jan 2024
- License
- MIT
- Provider
- BAAI
- KYI Score
- 9.1/10
Best For
Performance Metrics
Speed
Quality
Cost Efficiency
Specifications
- Parameters
- 568M
- License
- MIT
- Pricing
- free
- Release Date
- January 30, 2024
- Category
- llm
Key Features
Pros & Cons
Pros
- ✓Exceptional versatility
- ✓Multilingual
- ✓MIT license
- ✓State-of-the-art
Cons
- !Embedding only
- !Larger than some alternatives
Ideal Use Cases
Multilingual search
RAG
Retrieval
Clustering
BGE M3 FAQ
What is BGE M3 best used for?
BGE M3 excels at Multilingual search, RAG, Retrieval. Exceptional versatility, making it ideal for production applications requiring llm capabilities.
How does BGE M3 compare to other models?
BGE M3 has a KYI score of 9.1/10, with 568M parameters. It offers exceptional versatility and multilingual. Check our comparison pages for detailed benchmarks.
What are the system requirements for BGE M3?
BGE M3 with 568M requires appropriate GPU memory. Smaller quantized versions can run on consumer hardware, while full precision models need enterprise GPUs. Context length is variable.
Is BGE M3 free to use?
Yes, BGE M3 is free and licensed under MIT. You can deploy it on your own infrastructure without usage fees or API costs, giving you full control over your AI deployment.
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