Contextual AI Rerank v2 Instruct vs Voyage AI Rerank 2.5 Lite

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

Model Comparison

Two competitive rerankers, closely matched.

Both Contextual AI Rerank v2 Instruct and Voyage AI Rerank 2.5 Lite are powerful reranking models designed to improve retrieval quality in RAG applications. They show comparable performance across key metrics.

Key similarities:

  • Contextual AI Rerank v2 Instruct has 40 higher ELO rating
  • Voyage AI Rerank 2.5 Lite is 2403ms faster on average
  • Voyage AI Rerank 2.5 Lite has a 5.1% higher win rate

Overview

Key metrics

ELO Rating

Overall ranking quality

Contextual AI Rerank v2 Instruct

1550

Voyage AI Rerank 2.5 Lite

1510

Win Rate

Head-to-head performance

Contextual AI Rerank v2 Instruct

45.2%

Voyage AI Rerank 2.5 Lite

50.4%

Accuracy (nDCG@10)

Ranking quality metric

Contextual AI Rerank v2 Instruct

0.687

Voyage AI Rerank 2.5 Lite

0.679

Average Latency

Response time

Contextual AI Rerank v2 Instruct

3010ms

Voyage AI Rerank 2.5 Lite

607ms

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

MetricContextual AI Rerank v2 InstructVoyage AI Rerank 2.5 LiteDescription
Overall Performance
ELO Rating
1550
1510
Overall ranking quality based on pairwise comparisons
Win Rate
45.2%
50.4%
Percentage of comparisons won against other models
Pricing & Availability
Price per 1M tokens
$0.050
$0.020
Cost per million tokens processed
Release Date
2025-09-12
2025-08-11
Model release date
Accuracy Metrics
Avg nDCG@10
0.687
0.679
Normalized discounted cumulative gain at position 10
Performance Metrics
Avg Latency
3010ms
607ms
Average response time across all datasets

Dataset Performance

By field

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

FiQa

MetricContextual AI Rerank v2 InstructVoyage AI Rerank 2.5 LiteDescription
Accuracy Metrics
nDCG@5
0.119
0.111
Ranking quality at top 5 results
nDCG@10
0.125
0.122
Ranking quality at top 10 results
Recall@5
0.123
0.103
% of relevant docs in top 5
Recall@10
0.135
0.135
% of relevant docs in top 10
Latency Metrics
Mean
2913ms
686ms
Average response time
P50
2863ms
611ms
50th percentile (median)
P90
3289ms
829ms
90th percentile

PG

MetricContextual AI Rerank v2 InstructVoyage AI Rerank 2.5 LiteDescription
Accuracy Metrics
Latency Metrics
Mean
3195ms
637ms
Average response time
P50
2951ms
614ms
50th percentile (median)
P90
3781ms
817ms
90th percentile

business reports

MetricContextual AI Rerank v2 InstructVoyage AI Rerank 2.5 LiteDescription
Accuracy Metrics
Latency Metrics
Mean
2883ms
580ms
Average response time
P50
2686ms
607ms
50th percentile (median)
P90
3161ms
816ms
90th percentile

MSMARCO

MetricContextual AI Rerank v2 InstructVoyage AI Rerank 2.5 LiteDescription
Accuracy Metrics
nDCG@5
0.975
0.981
Ranking quality at top 5 results
nDCG@10
0.975
0.983
Ranking quality at top 10 results
Recall@5
1.000
0.993
% of relevant docs in top 5
Recall@10
1.000
1.000
% of relevant docs in top 10
Latency Metrics
Mean
2952ms
542ms
Average response time
P50
2853ms
611ms
50th percentile (median)
P90
3398ms
635ms
90th percentile

DBPedia

MetricContextual AI Rerank v2 InstructVoyage AI Rerank 2.5 LiteDescription
Accuracy Metrics
nDCG@5
0.734
0.692
Ranking quality at top 5 results
nDCG@10
0.772
0.763
Ranking quality at top 10 results
Recall@5
0.067
0.064
% of relevant docs in top 5
Recall@10
0.108
0.111
% of relevant docs in top 10
Latency Metrics
Mean
2803ms
555ms
Average response time
P50
2786ms
605ms
50th percentile (median)
P90
3138ms
664ms
90th percentile

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