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Comparison of bge-m3, Nemotron-3-Embed-1B-BF16
2 modelsBAAIbge-m3Remove ×nvidiaNemotron-3-Embed-1B-BF16Remove ×
What’s differentBGE-M3 is a versatile text embedding model that supports multi-functionality, multi-linguality, and multi-granularity, allowing it to perform dense retrieval, multi-vector retrieval, and sparse retrieval in…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…
DateMay 27, 2024ListedJul 15, 2026Listed
Listed rate$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗See provider quotes
Provider endpoints1 endpoint →0 endpoints →
FreshStack · MTEB 2.14.3 ↗MTEB 2.14.3; test/default; dataset 7a20df1aNot reported0.4173 ↗Revision f8801746; test/defaultContributor reported
Context window8.2K32.8K
Max output7.4K—
Parameters—1B
Open weightsSupportedNot reported

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