Microsoft (via Hugging Face)

E5-large-v2

Robust open-source embeddings for diverse search tasks.

Strong performance on retrieval benchmarWidely adopted in researchGood general-purpose semantic understandOpen-source availability
Today's score
94.0
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Where it ranks today

Best for / Not great for

Best for
  • General semantic search
  • RAG implementations
  • Academic research
  • Fine-tuning for specific domains
Not great for
  • Multilingual use cases without specific fine-tuning
  • Highly optimized, low-latency production systems without significant engineering
  • Users who prefer managed commercial APIs

Why it ranks here

E5-large-v2 remains a benchmark standard in the open-source community for retrieval tasks. Its solid performance and accessibility via Hugging Face continue to make it a popular choice, especially for researchers and developers building custom RAG systems who can leverage its flexibility.

30-day trend

Score breakdown

Search trends96
Benchmarks95
Developer buzz93
News mentions93

Pricing

API: $0.00 in · $0.00 out per 1M tokens · Consumer: $0.00/mo

Pricing plans

Popular
Open Source
Free and accessible model weights.
Free
  • Model weights available
  • Self-hosting required
  • Community support
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Cloud Provider Inference
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Custom
  • Pay for compute resources
  • Scalable infrastructure
  • Managed deployments
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Compare with another modelHow is this score calculated? →Snapshot 2026-08-11