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Comparison of multilingual-e5-large-instruct, mistral-embed, bge-m3-multi-8k
3 modelsintfloatmultilingual-e5-large-instructRemove ×Unknownmistral-embedRemove ×BAAIbge-m3-multi-8kRemove ×
What’s differentThe Multilingual-E5 models, initialized from XLM-RoBERTa, support up to 512 tokens per input — any longer text will be silently truncated. To ensure optimal performance, always prefix inputs with “query:”…8.2K contextBGE-M3 is a multilingual text embedding model developed by BAAI, distinguished by its Multi-Linguality (supporting 100+ languages), Multi-Functionality (unified dense, multi-vector, and sparse retrieval),…
DateApr 17, 2025ListedOct 16, 2026DiscoveredSep 3, 2026Listed
Listed rateSee provider quotes$0.10 in / $0.00 out/ 1M tokensExperiential · all routes ↗Standard list rateSee provider quotes
Provider endpoints0 endpoints →1 endpoint →0 endpoints →
Context window5128.2K8.2K
Max output———
Parameters———

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