Voyage 3 Large vs OpenAI text-embedding-3-small
Detailed comparison between Voyage 3 Large and OpenAI text-embedding-3-small. See which embedding best meets your accuracy and performance needs.
Model Comparison
Voyage 3 Large takes the lead.
Both Voyage 3 Large and OpenAI text-embedding-3-small are powerful embedding models designed to improve retrieval quality in RAG applications. However, their performance characteristics differ in important ways.
Why Voyage 3 Large:
- Voyage 3 Large has 25 higher ELO rating
- Voyage 3 Large delivers better accuracy (nDCG@10: 0.837 vs 0.762)
- Voyage 3 Large has a 8.0% higher win rate
Overview
Key metrics
ELO Rating
Overall ranking quality
Voyage 3 Large
OpenAI text-embedding-3-small
Win Rate
Head-to-head performance
Voyage 3 Large
OpenAI text-embedding-3-small
Accuracy (nDCG@10)
Ranking quality metric
Voyage 3 Large
OpenAI text-embedding-3-small
Average Latency
Response time
Voyage 3 Large
OpenAI text-embedding-3-small
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-small | Description |
|---|---|---|---|
| Overall Performance | |||
| ELO Rating | 1528 | 1503 | Overall ranking quality based on pairwise comparisons |
| Win Rate | 52.6% | 44.6% | Percentage of comparisons won against other models |
| Pricing & Availability | |||
| Price per 1M tokens | $0.180 | $0.020 | Cost per million tokens processed |
| Dimensions | 1024 | 1536 | Vector embedding dimensions (lower is more efficient) |
| Release Date | 2025-01-07 | 2024-01-25 | Model release date |
| Accuracy Metrics | |||
| Avg nDCG@10 | 0.837 | 0.762 | Normalized discounted cumulative gain at position 10 |
| Performance Metrics | |||
| Avg Latency | 29ms | 10ms | 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-small | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| Latency Metrics | |||
| Mean | 16ms | 9ms | Average response time |
| P50 | 16ms | 9ms | 50th percentile (median) |
| P90 | 18ms | 11ms | 90th percentile |
business reports
| Metric | Voyage 3 Large | OpenAI text-embedding-3-small | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| Latency Metrics | |||
| Mean | 30ms | 7ms | Average response time |
| P50 | 30ms | 7ms | 50th percentile (median) |
| P90 | 35ms | 8ms | 90th percentile |
DBPedia
| Metric | Voyage 3 Large | OpenAI text-embedding-3-small | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.675 | 0.605 | Ranking quality at top 5 results |
| nDCG@10 | 0.638 | 0.604 | Ranking quality at top 10 results |
| Recall@5 | 0.255 | 0.230 | % of relevant docs in top 5 |
| Recall@10 | 0.362 | 0.365 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 19ms | 7ms | Average response time |
| P50 | 19ms | 7ms | 50th percentile (median) |
| P90 | 22ms | 8ms | 90th percentile |
FiQa
| Metric | Voyage 3 Large | OpenAI text-embedding-3-small | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.753 | 0.635 | Ranking quality at top 5 results |
| nDCG@10 | 0.780 | 0.647 | Ranking quality at top 10 results |
| Recall@5 | 0.742 | 0.623 | % of relevant docs in top 5 |
| Recall@10 | 0.837 | 0.681 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 16ms | 8ms | Average response time |
| P50 | 16ms | 8ms | 50th percentile (median) |
| P90 | 18ms | 9ms | 90th percentile |
SciFact
| Metric | Voyage 3 Large | OpenAI text-embedding-3-small | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.796 | 0.682 | Ranking quality at top 5 results |
| nDCG@10 | 0.809 | 0.707 | Ranking quality at top 10 results |
| Recall@5 | 0.840 | 0.778 | % of relevant docs in top 5 |
| Recall@10 | 0.880 | 0.843 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 18ms | 11ms | Average response time |
| P50 | 18ms | 11ms | 50th percentile (median) |
| P90 | 21ms | 13ms | 90th percentile |
MSMARCO
| Metric | Voyage 3 Large | OpenAI text-embedding-3-small | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.997 | 0.997 | Ranking quality at top 5 results |
| nDCG@10 | 0.998 | 0.990 | Ranking quality at top 10 results |
| Recall@5 | 0.122 | 0.122 | % of relevant docs in top 5 |
| Recall@10 | 0.222 | 0.213 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 15ms | 7ms | Average response time |
| P50 | 15ms | 7ms | 50th percentile (median) |
| P90 | 17ms | 8ms | 90th percentile |
NorQuAD
| Metric | Voyage 3 Large | OpenAI text-embedding-3-small | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| Latency Metrics | |||
| Mean | 24ms | 16ms | Average response time |
| P50 | 23ms | 15ms | 50th percentile (median) |
| P90 | 28ms | 18ms | 90th percentile |
ARCD
| Metric | Voyage 3 Large | OpenAI text-embedding-3-small | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.953 | 0.855 | Ranking quality at top 5 results |
| nDCG@10 | 0.960 | 0.862 | Ranking quality at top 10 results |
| Recall@5 | 0.960 | 0.900 | % of relevant docs in top 5 |
| Recall@10 | 0.980 | 0.920 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 97ms | 11ms | Average response time |
| P50 | 95ms | 10ms | 50th percentile (median) |
| P90 | 112ms | 12ms | 90th percentile |
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