Voyage 3.5 vs Jina Embeddings v3

Detailed comparison between Voyage 3.5 and Jina Embeddings v3. See which embedding best meets your accuracy and performance needs.

Model Comparison

Voyage 3.5 takes the lead.

Both Voyage 3.5 and Jina Embeddings v3 are powerful embedding models designed to improve retrieval quality in RAG applications. However, their performance characteristics differ in important ways.

Why Voyage 3.5:

  • Voyage 3.5 has 24 higher ELO rating
  • Voyage 3.5 delivers better accuracy (nDCG@10: 0.816 vs 0.766)
  • Voyage 3.5 is 71ms faster on average
  • Voyage 3.5 has a 8.5% higher win rate

Overview

Key metrics

ELO Rating

Overall ranking quality

Voyage 3.5

1515

Jina Embeddings v3

1491

Win Rate

Head-to-head performance

Voyage 3.5

48.8%

Jina Embeddings v3

40.3%

Accuracy (nDCG@10)

Ranking quality metric

Voyage 3.5

0.816

Jina Embeddings v3

0.766

Average Latency

Response time

Voyage 3.5

13ms

Jina Embeddings v3

85ms

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

MetricVoyage 3.5Jina Embeddings v3Description
Overall Performance
ELO Rating
1515
1491
Overall ranking quality based on pairwise comparisons
Win Rate
48.8%
40.3%
Percentage of comparisons won against other models
Pricing & Availability
Price per 1M tokens
$0.060
$0.045
Cost per million tokens processed
Dimensions
1024
1024
Vector embedding dimensions (lower is more efficient)
Release Date
2025-05-20
2024-09-18
Model release date
Accuracy Metrics
Avg nDCG@10
0.816
0.766
Normalized discounted cumulative gain at position 10
Performance Metrics
Avg Latency
13ms
85ms
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

MetricVoyage 3.5Jina Embeddings v3Description
Accuracy Metrics
Latency Metrics
Mean
10ms
26ms
Average response time
P50
10ms
26ms
50th percentile (median)
P90
12ms
30ms
90th percentile

business reports

MetricVoyage 3.5Jina Embeddings v3Description
Accuracy Metrics
Latency Metrics
Mean
16ms
25ms
Average response time
P50
15ms
25ms
50th percentile (median)
P90
18ms
29ms
90th percentile

DBPedia

MetricVoyage 3.5Jina Embeddings v3Description
Accuracy Metrics
nDCG@5
0.655
0.616
Ranking quality at top 5 results
nDCG@10
0.637
0.591
Ranking quality at top 10 results
Recall@5
0.246
0.225
% of relevant docs in top 5
Recall@10
0.366
0.340
% of relevant docs in top 10
Latency Metrics
Mean
6ms
39ms
Average response time
P50
6ms
38ms
50th percentile (median)
P90
7ms
45ms
90th percentile

FiQa

MetricVoyage 3.5Jina Embeddings v3Description
Accuracy Metrics
nDCG@5
0.721
0.645
Ranking quality at top 5 results
nDCG@10
0.741
0.679
Ranking quality at top 10 results
Recall@5
0.715
0.633
% of relevant docs in top 5
Recall@10
0.793
0.741
% of relevant docs in top 10
Latency Metrics
Mean
9ms
89ms
Average response time
P50
9ms
87ms
50th percentile (median)
P90
11ms
102ms
90th percentile

SciFact

MetricVoyage 3.5Jina Embeddings v3Description
Accuracy Metrics
nDCG@5
0.723
0.622
Ranking quality at top 5 results
nDCG@10
0.751
0.661
Ranking quality at top 10 results
Recall@5
0.778
0.695
% of relevant docs in top 5
Recall@10
0.853
0.800
% of relevant docs in top 10
Latency Metrics
Mean
14ms
53ms
Average response time
P50
13ms
52ms
50th percentile (median)
P90
16ms
61ms
90th percentile

MSMARCO

MetricVoyage 3.5Jina Embeddings v3Description
Accuracy Metrics
nDCG@5
1.000
1.000
Ranking quality at top 5 results
nDCG@10
1.000
0.997
Ranking quality at top 10 results
Recall@5
0.123
0.123
% of relevant docs in top 5
Recall@10
0.224
0.220
% of relevant docs in top 10
Latency Metrics
Mean
10ms
92ms
Average response time
P50
9ms
90ms
50th percentile (median)
P90
11ms
106ms
90th percentile

NorQuAD

MetricVoyage 3.5Jina Embeddings v3Description
Accuracy Metrics
Latency Metrics
Mean
20ms
117ms
Average response time
P50
19ms
115ms
50th percentile (median)
P90
22ms
135ms
90th percentile

ARCD

MetricVoyage 3.5Jina Embeddings v3Description
Accuracy Metrics
nDCG@5
0.950
0.888
Ranking quality at top 5 results
nDCG@10
0.950
0.900
Ranking quality at top 10 results
Recall@5
0.980
0.920
% of relevant docs in top 5
Recall@10
0.980
0.960
% of relevant docs in top 10
Latency Metrics
Mean
23ms
236ms
Average response time
P50
23ms
232ms
50th percentile (median)
P90
27ms
272ms
90th percentile

Explore More

Compare more embeddings

See how all embedding models stack up. Compare OpenAI, Cohere, Jina AI, Voyage, and more. View comprehensive benchmarks, compare performance metrics, and find the perfect embedding for your RAG application.