Cohere Rerank 3.5 vs Contextual AI Rerank v2 Instruct

Detailed comparison between Cohere Rerank 3.5 and Contextual AI Rerank v2 Instruct. See which reranker best meets your accuracy and performance needs.

Model Comparison

Contextual AI Rerank v2 Instruct takes the lead.

Both Cohere Rerank 3.5 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 Contextual AI Rerank v2 Instruct:

  • Contextual AI Rerank v2 Instruct has 24 higher ELO rating
  • Contextual AI Rerank v2 Instruct delivers better accuracy (nDCG@10: 0.114 vs 0.080)

Overview

Key metrics

ELO Rating

Overall ranking quality

Cohere Rerank 3.5

1457

Contextual AI Rerank v2 Instruct

1481

Win Rate

Head-to-head performance

Cohere Rerank 3.5

43.7%

Contextual AI Rerank v2 Instruct

45.1%

Accuracy (nDCG@10)

Ranking quality metric

Cohere Rerank 3.5

0.080

Contextual AI Rerank v2 Instruct

0.114

Average Latency

Response time

Cohere Rerank 3.5

392ms

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

MetricCohere Rerank 3.5Contextual AI Rerank v2 InstructDescription
Overall Performance
ELO Rating
1457
1481
Overall ranking quality based on pairwise comparisons
Win Rate
43.7%
45.1%
Percentage of comparisons won against other models
Pricing & Availability
Price per 1M tokens
$0.050
$0.050
Cost per million tokens processed
Release Date
2024-12-02
2025-09-12
Model release date
Accuracy Metrics
Avg nDCG@10
0.080
0.114
Normalized discounted cumulative gain at position 10
Performance Metrics
Avg Latency
392ms
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

MetricCohere Rerank 3.5Contextual AI Rerank v2 InstructDescription
Latency Metrics
Mean
339ms
3283ms
Average response time
P50
285ms
3260ms
50th percentile (median)
P90
304ms
3885ms
90th percentile

arguana

MetricCohere Rerank 3.5Contextual AI Rerank v2 InstructDescription
Accuracy Metrics
nDCG@5
0.267
0.525
Ranking quality at top 5 results
nDCG@10
0.355
0.560
Ranking quality at top 10 results
Recall@5
0.520
0.860
% of relevant docs in top 5
Recall@10
0.800
0.960
% of relevant docs in top 10
Latency Metrics
Mean
570ms
3627ms
Average response time
P50
373ms
3601ms
50th percentile (median)
P90
617ms
4037ms
90th percentile

FiQa

MetricCohere Rerank 3.5Contextual AI Rerank v2 InstructDescription
Accuracy Metrics
nDCG@5
0.124
0.119
Ranking quality at top 5 results
nDCG@10
0.128
0.125
Ranking quality at top 10 results
Recall@5
0.123
0.123
% of relevant docs in top 5
Recall@10
0.130
0.135
% of relevant docs in top 10
Latency Metrics
Mean
364ms
3283ms
Average response time
P50
315ms
3209ms
50th percentile (median)
P90
401ms
3891ms
90th percentile

business reports

MetricCohere Rerank 3.5Contextual AI Rerank v2 InstructDescription
Latency Metrics
Mean
334ms
3231ms
Average response time
P50
293ms
3129ms
50th percentile (median)
P90
503ms
3651ms
90th percentile

PG

MetricCohere Rerank 3.5Contextual AI Rerank v2 InstructDescription
Latency Metrics
Mean
458ms
3566ms
Average response time
P50
360ms
3475ms
50th percentile (median)
P90
615ms
4148ms
90th percentile

DBPedia

MetricCohere Rerank 3.5Contextual AI Rerank v2 InstructDescription
Latency Metrics
Mean
286ms
3010ms
Average response time
P50
279ms
3042ms
50th percentile (median)
P90
290ms
3283ms
90th percentile

Explore More

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