BAAI/bge-m3 vs Gemini text-embedding-004
Detailed comparison between BAAI/bge-m3 and Gemini text-embedding-004. See which embedding best meets your accuracy and performance needs.
Model Comparison
BAAI/bge-m3 takes the lead.
Both BAAI/bge-m3 and Gemini text-embedding-004 are powerful embedding models designed to improve retrieval quality in RAG applications. However, their performance characteristics differ in important ways.
Why BAAI/bge-m3:
- BAAI/bge-m3 has 44 higher ELO rating
- BAAI/bge-m3 delivers better accuracy (nDCG@10: 0.753 vs 0.585)
- Gemini text-embedding-004 is 37774ms faster on average
- BAAI/bge-m3 has a 12.9% higher win rate
Overview
Key metrics
ELO Rating
Overall ranking quality
BAAI/bge-m3
Gemini text-embedding-004
Win Rate
Head-to-head performance
BAAI/bge-m3
Gemini text-embedding-004
Accuracy (nDCG@10)
Ranking quality metric
BAAI/bge-m3
Gemini text-embedding-004
Average Latency
Response time
BAAI/bge-m3
Gemini text-embedding-004
Visual Performance Analysis
Performance
ELO Rating Comparison
Win/Loss/Tie Breakdown
Accuracy Across Datasets (nDCG@10)
Latency Distribution (ms)
Breakdown
How the models stack up
| Metric | BAAI/bge-m3 | Gemini text-embedding-004 | Description |
|---|---|---|---|
| Overall Performance | |||
| ELO Rating | 1491 | 1447 | Overall ranking quality based on pairwise comparisons |
| Win Rate | 40.9% | 28.0% | Percentage of comparisons won against other models |
| Pricing & Availability | |||
| Price per 1M tokens | $0.010 | $0.020 | Cost per million tokens processed |
| Release Date | 2024-01-27 | 2024-05-14 | Model release date |
| Accuracy Metrics | |||
| Avg nDCG@10 | 0.753 | 0.585 | Normalized discounted cumulative gain at position 10 |
| Performance Metrics | |||
| Avg Latency | 80874ms | 43100ms | Average response time across all datasets |
Dataset Performance
By field
Comprehensive comparison of accuracy metrics (nDCG, Recall) and latency percentiles for each benchmark dataset.
PG
| Metric | BAAI/bge-m3 | Gemini text-embedding-004 | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| Latency Metrics | |||
| Mean | 96375ms | 76115ms | Average response time |
| P50 | 94448ms | 74593ms | 50th percentile (median) |
| P90 | 110831ms | 87532ms | 90th percentile |
business reports
| Metric | BAAI/bge-m3 | Gemini text-embedding-004 | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| Latency Metrics | |||
| Mean | 24163ms | 9184ms | Average response time |
| P50 | 23680ms | 9000ms | 50th percentile (median) |
| P90 | 27787ms | 10562ms | 90th percentile |
DBPedia
| Metric | BAAI/bge-m3 | Gemini text-embedding-004 | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.625 | 0.536 | Ranking quality at top 5 results |
| nDCG@10 | 0.603 | 0.517 | Ranking quality at top 10 results |
| Recall@5 | 0.236 | 0.200 | % of relevant docs in top 5 |
| Recall@10 | 0.341 | 0.304 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 86619ms | 59127ms | Average response time |
| P50 | 84887ms | 57944ms | 50th percentile (median) |
| P90 | 99612ms | 67996ms | 90th percentile |
FiQa
| Metric | BAAI/bge-m3 | Gemini text-embedding-004 | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.597 | 0.613 | Ranking quality at top 5 results |
| nDCG@10 | 0.609 | 0.649 | Ranking quality at top 10 results |
| Recall@5 | 0.607 | 0.645 | % of relevant docs in top 5 |
| Recall@10 | 0.666 | 0.748 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 159871ms | 62373ms | Average response time |
| P50 | 156674ms | 61126ms | 50th percentile (median) |
| P90 | 183852ms | 71729ms | 90th percentile |
SciFact
| Metric | BAAI/bge-m3 | Gemini text-embedding-004 | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.578 | 0.722 | Ranking quality at top 5 results |
| nDCG@10 | 0.617 | 0.745 | Ranking quality at top 10 results |
| Recall@5 | 0.652 | 0.797 | % of relevant docs in top 5 |
| Recall@10 | 0.763 | 0.860 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 154804ms | 65774ms | Average response time |
| P50 | 151708ms | 64459ms | 50th percentile (median) |
| P90 | 178025ms | 75640ms | 90th percentile |
MSMARCO
| Metric | BAAI/bge-m3 | Gemini text-embedding-004 | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.997 | 0.979 | Ranking quality at top 5 results |
| nDCG@10 | 0.997 | 0.977 | Ranking quality at top 10 results |
| Recall@5 | 0.122 | 0.118 | % of relevant docs in top 5 |
| Recall@10 | 0.220 | 0.209 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 96153ms | 62416ms | Average response time |
| P50 | 94230ms | 61168ms | 50th percentile (median) |
| P90 | 110576ms | 71778ms | 90th percentile |
NorQuAD
| Metric | BAAI/bge-m3 | Gemini text-embedding-004 | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| Latency Metrics | |||
| Mean | 16285ms | 5693ms | Average response time |
| P50 | 15959ms | 5579ms | 50th percentile (median) |
| P90 | 18728ms | 6547ms | 90th percentile |
ARCD
| Metric | BAAI/bge-m3 | Gemini text-embedding-004 | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.941 | 0.030 | Ranking quality at top 5 results |
| nDCG@10 | 0.941 | 0.036 | Ranking quality at top 10 results |
| Recall@5 | 0.960 | 0.040 | % of relevant docs in top 5 |
| Recall@10 | 0.960 | 0.060 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 12723ms | 4118ms | Average response time |
| P50 | 12469ms | 4036ms | 50th percentile (median) |
| P90 | 14631ms | 4736ms | 90th percentile |
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