Jina Embeddings v5 Text Small vs Voyage 3 Large

Detailed comparison between Jina Embeddings v5 Text Small and Voyage 3 Large. See which embedding best meets your accuracy and performance needs. If you want to compare these models on your data, try Agentset.

Model Comparison

Jina Embeddings v5 Text Small takes the lead.

Both Jina Embeddings v5 Text Small and Voyage 3 Large are powerful embedding models designed to improve retrieval quality in RAG applications. However, their performance characteristics differ in important ways.

Why Jina Embeddings v5 Text Small:

  • Jina Embeddings v5 Text Small has 32 higher ELO rating
  • Jina Embeddings v5 Text Small delivers better accuracy (nDCG@10: 0.608 vs 0.501)

Overview

Key metrics

ELO Rating

Overall ranking quality

Jina Embeddings v5 Text Small

1566

Voyage 3 Large

1534

Win Rate

Head-to-head performance

Jina Embeddings v5 Text Small

54.7%

Voyage 3 Large

51.3%

Accuracy (nDCG@10)

Ranking quality metric

Jina Embeddings v5 Text Small

0.608

Voyage 3 Large

0.501

Average Latency

Response time

Jina Embeddings v5 Text Small

289ms

Voyage 3 Large

272ms

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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

MetricJina Embeddings v5 Text SmallVoyage 3 LargeDescription
Overall Performance
ELO Rating
1566
1534
Overall ranking quality based on pairwise comparisons
Win Rate
54.7%
51.3%
Percentage of comparisons won against other models
Pricing & Availability
Price per 1M tokens
$0.050
$0.180
Cost per million tokens processed
Dimensions
1024
1024
Vector embedding dimensions (lower is more efficient)
Release Date
2026-02-18
2025-01-07
Model release date
Accuracy Metrics
Avg nDCG@10
0.608
0.501
Normalized discounted cumulative gain at position 10
Performance Metrics
Avg Latency
289ms
272ms
Average response time across all datasets

Build RAG in Minutes, Not Months

Agentset gives you a complete RAG API with top-ranked embedding models and smart retrieval built in. Upload your data, call the API, and get accurate results from day one.

import { Agentset } from "agentset";

const agentset = new Agentset();
const ns = agentset.namespace("ns_1234");

const results = await ns.search(
  "What is multi-head attention?"
);

for (const result of results) {
  console.log(result.text);
}

Dataset Performance

By field

Comprehensive comparison of accuracy metrics (nDCG, Recall) and latency percentiles for each benchmark dataset.

PG

MetricJina Embeddings v5 Text SmallVoyage 3 LargeDescription
Accuracy Metrics
nDCG@5
0.000
0.000
Ranking quality at top 5 results
nDCG@10
0.000
0.000
Ranking quality at top 10 results
Recall@5
0.000
0.000
% of relevant docs in top 5
Recall@10
0.000
0.000
% of relevant docs in top 10
Latency Metrics
Mean
291ms
307ms
Average response time
P50
241ms
307ms
50th percentile (median)
P90
290ms
307ms
90th percentile

business reports

MetricJina Embeddings v5 Text SmallVoyage 3 LargeDescription
Accuracy Metrics
nDCG@5
0.000
0.000
Ranking quality at top 5 results
nDCG@10
0.000
0.000
Ranking quality at top 10 results
Recall@5
0.000
0.000
% of relevant docs in top 5
Recall@10
0.000
0.000
% of relevant docs in top 10
Latency Metrics
Mean
283ms
309ms
Average response time
P50
247ms
309ms
50th percentile (median)
P90
322ms
309ms
90th percentile

DBPedia

MetricJina Embeddings v5 Text SmallVoyage 3 LargeDescription
Accuracy Metrics
nDCG@5
0.823
0.801
Ranking quality at top 5 results
nDCG@10
0.805
0.790
Ranking quality at top 10 results
Recall@5
0.062
0.062
% of relevant docs in top 5
Recall@10
0.123
0.123
% of relevant docs in top 10
Latency Metrics
Mean
270ms
188ms
Average response time
P50
239ms
188ms
50th percentile (median)
P90
264ms
188ms
90th percentile

FiQa

MetricJina Embeddings v5 Text SmallVoyage 3 LargeDescription
Accuracy Metrics
nDCG@5
0.838
0.000
Ranking quality at top 5 results
nDCG@10
0.831
0.000
Ranking quality at top 10 results
Recall@5
0.677
0.000
% of relevant docs in top 5
Recall@10
0.771
0.000
% of relevant docs in top 10
Latency Metrics
Mean
300ms
319ms
Average response time
P50
241ms
319ms
50th percentile (median)
P90
419ms
319ms
90th percentile

SciFact

MetricJina Embeddings v5 Text SmallVoyage 3 LargeDescription
Accuracy Metrics
nDCG@5
0.703
0.766
Ranking quality at top 5 results
nDCG@10
0.734
0.779
Ranking quality at top 10 results
Recall@5
0.789
0.837
% of relevant docs in top 5
Recall@10
0.898
0.878
% of relevant docs in top 10
Latency Metrics
Mean
267ms
230ms
Average response time
P50
240ms
230ms
50th percentile (median)
P90
265ms
230ms
90th percentile

MSMARCO

MetricJina Embeddings v5 Text SmallVoyage 3 LargeDescription
Accuracy Metrics
nDCG@5
0.960
0.956
Ranking quality at top 5 results
nDCG@10
0.954
0.942
Ranking quality at top 10 results
Recall@5
0.122
0.122
% of relevant docs in top 5
Recall@10
0.219
0.221
% of relevant docs in top 10
Latency Metrics
Mean
273ms
251ms
Average response time
P50
239ms
251ms
50th percentile (median)
P90
313ms
251ms
90th percentile

ARCD

MetricJina Embeddings v5 Text SmallVoyage 3 LargeDescription
Accuracy Metrics
nDCG@5
0.842
0.898
Ranking quality at top 5 results
nDCG@10
0.842
0.905
Ranking quality at top 10 results
Recall@5
0.940
0.960
% of relevant docs in top 5
Recall@10
0.940
0.980
% of relevant docs in top 10
Latency Metrics
Mean
336ms
300ms
Average response time
P50
248ms
300ms
50th percentile (median)
P90
305ms
300ms
90th percentile

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