OpenAI text-embedding-3-large vs Cohere Embed v3
Detailed comparison between OpenAI text-embedding-3-large and Cohere Embed v3. See which embedding best meets your accuracy and performance needs.
Model Comparison
OpenAI text-embedding-3-large takes the lead.
Both OpenAI text-embedding-3-large and Cohere Embed v3 are powerful embedding models designed to improve retrieval quality in RAG applications. However, their performance characteristics differ in important ways.
Why OpenAI text-embedding-3-large:
- OpenAI text-embedding-3-large has 50 higher ELO rating
- OpenAI text-embedding-3-large delivers better accuracy (nDCG@10: 0.811 vs 0.686)
- Cohere Embed v3 is 10073ms faster on average
- OpenAI text-embedding-3-large has a 14.7% higher win rate
Overview
Key metrics
ELO Rating
Overall ranking quality
OpenAI text-embedding-3-large
Cohere Embed v3
Win Rate
Head-to-head performance
OpenAI text-embedding-3-large
Cohere Embed v3
Accuracy (nDCG@10)
Ranking quality metric
OpenAI text-embedding-3-large
Cohere Embed v3
Average Latency
Response time
OpenAI text-embedding-3-large
Cohere Embed v3
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 | OpenAI text-embedding-3-large | Cohere Embed v3 | Description |
|---|---|---|---|
| Overall Performance | |||
| ELO Rating | 1539 | 1488 | Overall ranking quality based on pairwise comparisons |
| Win Rate | 55.7% | 41.0% | Percentage of comparisons won against other models |
| Pricing & Availability | |||
| Price per 1M tokens | $0.130 | $0.100 | Cost per million tokens processed |
| Release Date | 2024-01-25 | 2024-02-07 | Model release date |
| Accuracy Metrics | |||
| Avg nDCG@10 | 0.811 | 0.686 | Normalized discounted cumulative gain at position 10 |
| Performance Metrics | |||
| Avg Latency | 32922ms | 22849ms | 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 | OpenAI text-embedding-3-large | Cohere Embed v3 | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| Latency Metrics | |||
| Mean | 57366ms | 35998ms | Average response time |
| P50 | 56219ms | 35278ms | 50th percentile (median) |
| P90 | 65971ms | 41398ms | 90th percentile |
business reports
| Metric | OpenAI text-embedding-3-large | Cohere Embed v3 | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| Latency Metrics | |||
| Mean | 8013ms | 4704ms | Average response time |
| P50 | 7853ms | 4610ms | 50th percentile (median) |
| P90 | 9215ms | 5410ms | 90th percentile |
DBPedia
| Metric | OpenAI text-embedding-3-large | Cohere Embed v3 | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.648 | 0.634 | Ranking quality at top 5 results |
| nDCG@10 | 0.641 | 0.619 | Ranking quality at top 10 results |
| Recall@5 | 0.255 | 0.219 | % of relevant docs in top 5 |
| Recall@10 | 0.377 | 0.353 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 42058ms | 30356ms | Average response time |
| P50 | 41217ms | 29749ms | 50th percentile (median) |
| P90 | 48367ms | 34909ms | 90th percentile |
FiQa
| Metric | OpenAI text-embedding-3-large | Cohere Embed v3 | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.730 | 0.641 | Ranking quality at top 5 results |
| nDCG@10 | 0.752 | 0.650 | Ranking quality at top 10 results |
| Recall@5 | 0.700 | 0.639 | % of relevant docs in top 5 |
| Recall@10 | 0.781 | 0.678 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 48635ms | 33241ms | Average response time |
| P50 | 47662ms | 32576ms | 50th percentile (median) |
| P90 | 55930ms | 38227ms | 90th percentile |
SciFact
| Metric | OpenAI text-embedding-3-large | Cohere Embed v3 | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.726 | 0.729 | Ranking quality at top 5 results |
| nDCG@10 | 0.761 | 0.769 | Ranking quality at top 10 results |
| Recall@5 | 0.768 | 0.788 | % of relevant docs in top 5 |
| Recall@10 | 0.863 | 0.900 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 55796ms | 41205ms | Average response time |
| P50 | 54680ms | 40381ms | 50th percentile (median) |
| P90 | 64165ms | 47386ms | 90th percentile |
MSMARCO
| Metric | OpenAI text-embedding-3-large | Cohere Embed v3 | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 1.000 | 1.000 | Ranking quality at top 5 results |
| nDCG@10 | 1.000 | 0.996 | Ranking quality at top 10 results |
| Recall@5 | 0.123 | 0.123 | % of relevant docs in top 5 |
| Recall@10 | 0.224 | 0.218 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 41860ms | 30494ms | Average response time |
| P50 | 41023ms | 29884ms | 50th percentile (median) |
| P90 | 48139ms | 35068ms | 90th percentile |
NorQuAD
| Metric | OpenAI text-embedding-3-large | Cohere Embed v3 | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| Latency Metrics | |||
| Mean | 5613ms | 3703ms | Average response time |
| P50 | 5501ms | 3629ms | 50th percentile (median) |
| P90 | 6455ms | 4258ms | 90th percentile |
ARCD
| Metric | OpenAI text-embedding-3-large | Cohere Embed v3 | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.899 | 0.349 | Ranking quality at top 5 results |
| nDCG@10 | 0.899 | 0.398 | Ranking quality at top 10 results |
| Recall@5 | 0.940 | 0.380 | % of relevant docs in top 5 |
| Recall@10 | 0.940 | 0.520 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 4036ms | 3093ms | Average response time |
| P50 | 3955ms | 3031ms | 50th percentile (median) |
| P90 | 4641ms | 3557ms | 90th percentile |
Explore More
Compare more embeddings
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