OpenAI text-embedding-3-large vs Qwen3 Embedding 4B
Detailed comparison between OpenAI text-embedding-3-large and Qwen3 Embedding 4B. 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 Qwen3 Embedding 4B 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 43 higher ELO rating
- OpenAI text-embedding-3-large is 47099ms faster on average
- OpenAI text-embedding-3-large has a 14.6% higher win rate
Overview
Key metrics
ELO Rating
Overall ranking quality
OpenAI text-embedding-3-large
Qwen3 Embedding 4B
Win Rate
Head-to-head performance
OpenAI text-embedding-3-large
Qwen3 Embedding 4B
Accuracy (nDCG@10)
Ranking quality metric
OpenAI text-embedding-3-large
Qwen3 Embedding 4B
Average Latency
Response time
OpenAI text-embedding-3-large
Qwen3 Embedding 4B
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 | Qwen3 Embedding 4B | Description |
|---|---|---|---|
| Overall Performance | |||
| ELO Rating | 1539 | 1496 | Overall ranking quality based on pairwise comparisons |
| Win Rate | 55.7% | 41.1% | Percentage of comparisons won against other models |
| Pricing & Availability | |||
| Price per 1M tokens | $0.130 | $0.020 | Cost per million tokens processed |
| Release Date | 2024-01-25 | 2025-06-06 | Model release date |
| Accuracy Metrics | |||
| Avg nDCG@10 | 0.811 | 0.802 | Normalized discounted cumulative gain at position 10 |
| Performance Metrics | |||
| Avg Latency | 32922ms | 80021ms | 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 | Qwen3 Embedding 4B | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| Latency Metrics | |||
| Mean | 57366ms | 107349ms | Average response time |
| P50 | 56219ms | 105202ms | 50th percentile (median) |
| P90 | 65971ms | 123451ms | 90th percentile |
business reports
| Metric | OpenAI text-embedding-3-large | Qwen3 Embedding 4B | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| Latency Metrics | |||
| Mean | 8013ms | 26100ms | Average response time |
| P50 | 7853ms | 25578ms | 50th percentile (median) |
| P90 | 9215ms | 30015ms | 90th percentile |
DBPedia
| Metric | OpenAI text-embedding-3-large | Qwen3 Embedding 4B | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.648 | 0.603 | Ranking quality at top 5 results |
| nDCG@10 | 0.641 | 0.595 | Ranking quality at top 10 results |
| Recall@5 | 0.255 | 0.234 | % of relevant docs in top 5 |
| Recall@10 | 0.377 | 0.375 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 42058ms | 106747ms | Average response time |
| P50 | 41217ms | 104612ms | 50th percentile (median) |
| P90 | 48367ms | 122759ms | 90th percentile |
FiQa
| Metric | OpenAI text-embedding-3-large | Qwen3 Embedding 4B | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.730 | 0.724 | Ranking quality at top 5 results |
| nDCG@10 | 0.752 | 0.759 | Ranking quality at top 10 results |
| Recall@5 | 0.700 | 0.715 | % of relevant docs in top 5 |
| Recall@10 | 0.781 | 0.835 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 48635ms | 120137ms | Average response time |
| P50 | 47662ms | 117734ms | 50th percentile (median) |
| P90 | 55930ms | 138158ms | 90th percentile |
SciFact
| Metric | OpenAI text-embedding-3-large | Qwen3 Embedding 4B | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.726 | 0.695 | Ranking quality at top 5 results |
| nDCG@10 | 0.761 | 0.733 | Ranking quality at top 10 results |
| Recall@5 | 0.768 | 0.787 | % of relevant docs in top 5 |
| Recall@10 | 0.863 | 0.893 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 55796ms | 143712ms | Average response time |
| P50 | 54680ms | 140838ms | 50th percentile (median) |
| P90 | 64165ms | 165269ms | 90th percentile |
MSMARCO
| Metric | OpenAI text-embedding-3-large | Qwen3 Embedding 4B | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 1.000 | 1.000 | Ranking quality at top 5 results |
| nDCG@10 | 1.000 | 1.000 | Ranking quality at top 10 results |
| Recall@5 | 0.123 | 0.123 | % of relevant docs in top 5 |
| Recall@10 | 0.224 | 0.224 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 41860ms | 112945ms | Average response time |
| P50 | 41023ms | 110686ms | 50th percentile (median) |
| P90 | 48139ms | 129887ms | 90th percentile |
NorQuAD
| Metric | OpenAI text-embedding-3-large | Qwen3 Embedding 4B | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| Latency Metrics | |||
| Mean | 5613ms | 13597ms | Average response time |
| P50 | 5501ms | 13325ms | 50th percentile (median) |
| P90 | 6455ms | 15637ms | 90th percentile |
ARCD
| Metric | OpenAI text-embedding-3-large | Qwen3 Embedding 4B | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.899 | 0.915 | Ranking quality at top 5 results |
| nDCG@10 | 0.899 | 0.922 | Ranking quality at top 10 results |
| Recall@5 | 0.940 | 0.940 | % of relevant docs in top 5 |
| Recall@10 | 0.940 | 0.960 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 4036ms | 9581ms | Average response time |
| P50 | 3955ms | 9389ms | 50th percentile (median) |
| P90 | 4641ms | 11018ms | 90th percentile |
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