The newest model in the Embedding Models Benchmarks is jina-v5-text-small.
Embedding Benchmarks
Transparent embedding models benchmarks built on AIMultiple's own retrieval evaluations of commercial and open-source embedding models across three enterprise RAG domains. See the methodology.
Leaderboard
Every benchmarked embedding model, ranked by its three-domain nDCG@3 average.
# | Model | nDCG@3 | CUAD (legal) | TechQA (support) | MedRAG (health) |
|---|---|---|---|---|---|
| 1 | voyage-3.5 Voyage AI | 0.943 | 0.910 | 0.965 | 0.954 |
| 2 | voyage-4-large Voyage AI | 0.942 | 0.873 | 0.966 | 0.986 |
| 3 | gemini-2-preview Google | 0.932 | 0.896 | 0.930 | 0.969 |
| 4 | nvidia-nemotron-8b NVIDIA | 0.925 | 0.860 | 0.952 | 0.963 |
| 5 | gemini-001 Google | 0.922 | 0.898 | 0.886 | 0.981 |
| 6 | voyage-4-lite Voyage AI | 0.921 | 0.859 | 0.948 | 0.956 |
| 7 | voyage-law-2 Voyage AI | 0.919 | 0.913 | 0.902 | 0.941 |
| 8 | SFR-Embedding-2_R Salesforce | 0.905 | 0.842 | 0.911 | 0.962 |
| 9 | jina-v5-text-small Jina AI | 0.895 | 0.836 | 0.897 | 0.952 |
| 10 | harrier-oss-0.6b Microsoft | 0.891 | 0.872 | 0.841 | 0.961 |
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How Embedding Models Benchmarks are Built
The embedding models benchmarks score each model by nDCG@3, the share of queries where the gold document lands in the top 3 results, and average its standing across the three retrieval domains it was evaluated on. Each benchmark below feeds that score.
Recent Updates
Latest changes to the Embedding Models Benchmarks, model coverage and AIMultiple benchmark methodology.
jina-v5-text-small
New model added to the Embedding Models Benchmarks.
harrier-oss-0.6b
New model added to the Embedding Models Benchmarks.
gemini-2-preview
New model added to the Embedding Models Benchmarks.
voyage-4-large
New model added to the Embedding Models Benchmarks.