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