Voyage AI Rerank 2.5 Lite vs Contextual AI Rerank v2 Instruct

Detailed comparison between Voyage AI Rerank 2.5 Lite and Contextual AI Rerank v2 Instruct. See which reranker best meets your accuracy and performance needs.

Model Comparison

Voyage AI Rerank 2.5 Lite takes the lead.

Both Voyage AI Rerank 2.5 Lite and Contextual AI Rerank v2 Instruct are powerful reranking models designed to improve retrieval quality in RAG applications. However, their performance characteristics differ in important ways.

Why Voyage AI Rerank 2.5 Lite:

  • Voyage AI Rerank 2.5 Lite has 68 higher ELO rating
  • Voyage AI Rerank 2.5 Lite is 2718ms faster on average
  • Voyage AI Rerank 2.5 Lite has a 11.4% higher win rate

Overview

Key metrics

ELO Rating

Overall ranking quality

Voyage AI Rerank 2.5 Lite

1549

Contextual AI Rerank v2 Instruct

1481

Win Rate

Head-to-head performance

Voyage AI Rerank 2.5 Lite

56.5%

Contextual AI Rerank v2 Instruct

45.1%

Accuracy (nDCG@10)

Ranking quality metric

Voyage AI Rerank 2.5 Lite

0.103

Contextual AI Rerank v2 Instruct

0.114

Average Latency

Response time

Voyage AI Rerank 2.5 Lite

616ms

Contextual AI Rerank v2 Instruct

3333ms

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 AI Rerank 2.5 LiteContextual AI Rerank v2 InstructDescription
Overall Performance
ELO Rating
1549
1481
Overall ranking quality based on pairwise comparisons
Win Rate
56.5%
45.1%
Percentage of comparisons won against other models
Pricing & Availability
Price per 1M tokens
$0.020
$0.050
Cost per million tokens processed
Release Date
2025-08-11
2025-09-12
Model release date
Accuracy Metrics
Avg nDCG@10
0.103
0.114
Normalized discounted cumulative gain at position 10
Performance Metrics
Avg Latency
616ms
3333ms
Average response time across all datasets

Dataset Performance

By field

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

MSMARCO

MetricVoyage AI Rerank 2.5 LiteContextual AI Rerank v2 InstructDescription
Latency Metrics
Mean
563ms
3283ms
Average response time
P50
610ms
3260ms
50th percentile (median)
P90
619ms
3885ms
90th percentile

arguana

MetricVoyage AI Rerank 2.5 LiteContextual AI Rerank v2 InstructDescription
Accuracy Metrics
nDCG@5
0.436
0.525
Ranking quality at top 5 results
nDCG@10
0.496
0.560
Ranking quality at top 10 results
Recall@5
0.800
0.860
% of relevant docs in top 5
Recall@10
0.980
0.960
% of relevant docs in top 10
Latency Metrics
Mean
636ms
3627ms
Average response time
P50
613ms
3601ms
50th percentile (median)
P90
819ms
4037ms
90th percentile

FiQa

MetricVoyage AI Rerank 2.5 LiteContextual AI Rerank v2 InstructDescription
Accuracy Metrics
nDCG@5
0.111
0.119
Ranking quality at top 5 results
nDCG@10
0.122
0.125
Ranking quality at top 10 results
Recall@5
0.103
0.123
% of relevant docs in top 5
Recall@10
0.135
0.135
% of relevant docs in top 10
Latency Metrics
Mean
639ms
3283ms
Average response time
P50
613ms
3209ms
50th percentile (median)
P90
819ms
3891ms
90th percentile

business reports

MetricVoyage AI Rerank 2.5 LiteContextual AI Rerank v2 InstructDescription
Latency Metrics
Mean
599ms
3231ms
Average response time
P50
611ms
3129ms
50th percentile (median)
P90
727ms
3651ms
90th percentile

PG

MetricVoyage AI Rerank 2.5 LiteContextual AI Rerank v2 InstructDescription
Latency Metrics
Mean
670ms
3566ms
Average response time
P50
615ms
3475ms
50th percentile (median)
P90
818ms
4148ms
90th percentile

DBPedia

MetricVoyage AI Rerank 2.5 LiteContextual AI Rerank v2 InstructDescription
Latency Metrics
Mean
587ms
3010ms
Average response time
P50
612ms
3042ms
50th percentile (median)
P90
656ms
3283ms
90th percentile

Explore More

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