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Home / Models / E5 Large

E5 Large

by Microsoft

8.7
KYI Score

Text embedding model with strong performance on retrieval tasks.

LLMMITFREE335M
Official WebsiteHugging Face

Quick Facts

Model Size
335M
Context Length
N/A
Release Date
Dec 2022
License
MIT
Provider
Microsoft
KYI Score
8.7/10

Best For

→Semantic search
→RAG
→Document retrieval
→Clustering

Performance Metrics

Speed

9/10

Quality

8/10

Cost Efficiency

10/10

Specifications

Parameters
335M
License
MIT
Pricing
free
Release Date
December 15, 2022
Category
llm

Key Features

Text embeddingsRetrievalSemantic searchEfficient

Pros & Cons

Pros

  • ✓Good performance
  • ✓Fast
  • ✓MIT license
  • ✓Microsoft-backed

Cons

  • !Embedding only
  • !English-focused

Ideal Use Cases

Semantic search

RAG

Document retrieval

Clustering

E5 Large FAQ

What is E5 Large best used for?

E5 Large excels at Semantic search, RAG, Document retrieval. Good performance, making it ideal for production applications requiring llm capabilities.

How does E5 Large compare to other models?

E5 Large has a KYI score of 8.7/10, with 335M parameters. It offers good performance and fast. Check our comparison pages for detailed benchmarks.

What are the system requirements for E5 Large?

E5 Large with 335M requires appropriate GPU memory. Smaller quantized versions can run on consumer hardware, while full precision models need enterprise GPUs. Context length is variable.

Is E5 Large free to use?

Yes, E5 Large 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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