Sold by: Waltsoft Inc.
Deployed on AWS
8.6M monthly downloads. Smallest multilingual-E5 model at 117MB. High-throughput embedding for 100 languages in latency-constrained pipelines.
Overview
Multilingual-E5-Small is the smallest and fastest model in the multilingual-E5 family from Microsoft Research with 8.6 million monthly downloads. At just 117MB with 118M parameters, it delivers strong cross-lingual semantic alignment across 100 languages while enabling high-throughput inference -- ideal for pipelines that must embed thousands of documents per minute. Trained with E5's prefix-based contrastive learning (query: prefix for queries, passage: prefix for documents), it achieves surprisingly strong performance relative to its size on MTEB multilingual benchmarks. Enterprises use it as the embedding backbone for high-volume document indexing, multilingual product catalog search, and real-time multilingual support ticket routing where latency and cost matter.
Highlights
- 117MB -- smallest multilingual model with strong 100-language semantic alignment
- 8.6M monthly downloads; optimized for high-throughput document indexing pipelines
- E5 prefix contrastive training: use 'query:' prefix for queries, 'passage:' for documents
Details
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Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.xlarge Inference (Real-Time) Recommended | Model inference on the ml.m5.xlarge instance type, real-time mode | $0.10 |
ml.m5.xlarge Inference (Batch) Recommended | Model inference on the ml.m5.xlarge instance type, batch mode | $0.10 |
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
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Version release notes
Initial release
Additional details
Inputs
- Summary
8.6M monthly downloads. Smallest multilingual-E5 model at 117MB. High-throughput embedding for 100 languages in latency-constrained pipelines.
- Input MIME type
- application/json
https://waltsoft-marketplace-assets.s3.amazonaws.com/ml-validation/text-sample/sample.jsonl
https://waltsoft-marketplace-assets.s3.amazonaws.com/ml-validation/text-sample/sample.jsonl
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Contact support@waltsoft.net for deployment assistance.
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