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Comparison of multilingual-e5-large-instruct, Nemotron-3-Embed-1B-BF16
2 modelsintfloatmultilingual-e5-large-instructRemove ×nvidiaNemotron-3-Embed-1B-BF16Remove ×
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:”…Nemotron-3-Embed-1B-BF16 is a compact multilingual text embedding model from NVIDIA, pruned and distilled from Ministral-3 to ~1B parameters, that maps text into 2048-dimensional dense vectors for retrieval…
DateApr 17, 2025ListedJul 15, 2026Listed
Listed rateSee provider quotesSee provider quotes
Provider endpoints0 endpoints →0 endpoints →
FreshStack · MTEB 2.14.3 ↗MTEB 2.14.3; test/default; dataset 7a20df1aNot reported0.4173 ↗Revision f8801746; test/defaultContributor reported
Context window51232.8K
Max output——
Parameters—1B

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