Voyage 3 Large vs OpenAI text-embedding-3-large
Detailed comparison between Voyage 3 Large 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 Voyage 3 Large 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 11 higher ELO rating
- Voyage 3 Large delivers better accuracy (nDCG@10: 0.837 vs 0.811)
- OpenAI text-embedding-3-large is 30555ms faster on average
Overview
Key metrics
ELO Rating
Overall ranking quality
Voyage 3 Large
OpenAI text-embedding-3-large
Win Rate
Head-to-head performance
Voyage 3 Large
OpenAI text-embedding-3-large
Accuracy (nDCG@10)
Ranking quality metric
Voyage 3 Large
OpenAI text-embedding-3-large
Average Latency
Response time
Voyage 3 Large
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 | Voyage 3 Large | OpenAI text-embedding-3-large | Description |
|---|---|---|---|
| Overall Performance | |||
| ELO Rating | 1528 | 1539 | Overall ranking quality based on pairwise comparisons |
| Win Rate | 52.6% | 55.7% | Percentage of comparisons won against other models |
| Pricing & Availability | |||
| Price per 1M tokens | $0.180 | $0.130 | Cost per million tokens processed |
| Release Date | 2025-01-07 | 2024-01-25 | Model release date |
| Accuracy Metrics | |||
| Avg nDCG@10 | 0.837 | 0.811 | Normalized discounted cumulative gain at position 10 |
| Performance Metrics | |||
| Avg Latency | 63477ms | 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 | Voyage 3 Large | OpenAI text-embedding-3-large | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| Latency Metrics | |||
| Mean | 93447ms | 57366ms | Average response time |
| P50 | 91578ms | 56219ms | 50th percentile (median) |
| P90 | 107464ms | 65971ms | 90th percentile |
business reports
| Metric | Voyage 3 Large | OpenAI text-embedding-3-large | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| Latency Metrics | |||
| Mean | 21279ms | 8013ms | Average response time |
| P50 | 20853ms | 7853ms | 50th percentile (median) |
| P90 | 24471ms | 9215ms | 90th percentile |
DBPedia
| Metric | Voyage 3 Large | OpenAI text-embedding-3-large | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.675 | 0.648 | Ranking quality at top 5 results |
| nDCG@10 | 0.638 | 0.641 | Ranking quality at top 10 results |
| Recall@5 | 0.255 | 0.255 | % of relevant docs in top 5 |
| Recall@10 | 0.362 | 0.377 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 97066ms | 42058ms | Average response time |
| P50 | 95125ms | 41217ms | 50th percentile (median) |
| P90 | 111626ms | 48367ms | 90th percentile |
FiQa
| Metric | Voyage 3 Large | OpenAI text-embedding-3-large | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.753 | 0.730 | Ranking quality at top 5 results |
| nDCG@10 | 0.780 | 0.752 | Ranking quality at top 10 results |
| Recall@5 | 0.742 | 0.700 | % of relevant docs in top 5 |
| Recall@10 | 0.837 | 0.781 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 80239ms | 48635ms | Average response time |
| P50 | 78634ms | 47662ms | 50th percentile (median) |
| P90 | 92275ms | 55930ms | 90th percentile |
SciFact
| Metric | Voyage 3 Large | OpenAI text-embedding-3-large | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.796 | 0.726 | Ranking quality at top 5 results |
| nDCG@10 | 0.809 | 0.761 | Ranking quality at top 10 results |
| Recall@5 | 0.840 | 0.768 | % of relevant docs in top 5 |
| Recall@10 | 0.880 | 0.863 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 92317ms | 55796ms | Average response time |
| P50 | 90471ms | 54680ms | 50th percentile (median) |
| P90 | 106165ms | 64165ms | 90th percentile |
MSMARCO
| Metric | Voyage 3 Large | OpenAI text-embedding-3-large | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.997 | 1.000 | Ranking quality at top 5 results |
| nDCG@10 | 0.998 | 1.000 | Ranking quality at top 10 results |
| Recall@5 | 0.122 | 0.123 | % of relevant docs in top 5 |
| Recall@10 | 0.222 | 0.224 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 75502ms | 41860ms | Average response time |
| P50 | 73992ms | 41023ms | 50th percentile (median) |
| P90 | 86827ms | 48139ms | 90th percentile |
NorQuAD
| Metric | Voyage 3 Large | OpenAI text-embedding-3-large | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| Latency Metrics | |||
| Mean | 11003ms | 5613ms | Average response time |
| P50 | 10783ms | 5501ms | 50th percentile (median) |
| P90 | 12653ms | 6455ms | 90th percentile |
ARCD
| Metric | Voyage 3 Large | OpenAI text-embedding-3-large | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.953 | 0.899 | Ranking quality at top 5 results |
| nDCG@10 | 0.960 | 0.899 | Ranking quality at top 10 results |
| Recall@5 | 0.960 | 0.940 | % of relevant docs in top 5 |
| Recall@10 | 0.980 | 0.940 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 36963ms | 4036ms | Average response time |
| P50 | 36224ms | 3955ms | 50th percentile (median) |
| P90 | 42507ms | 4641ms | 90th percentile |
Explore More
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