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Cohere Rerank 3.5

Advanced reranking model with improved reasoning and multilingual capabilities for enterprise data. Excels in complex enterprise scenarios including Finance, E-commerce, and Hospitality across 100+ languages. If you want to compare the best rerankers for your data, try Agentset.

Leaderboard Rank
#10
of 12
ELO Rating
1451
#10
Win Rate
40.9%
#10
Accuracy (nDCG@10)
0.080
#11
Latency
392ms
#4

Model Information

Provider
Cohere
License
Proprietary
Price per 1M tokens
$0.050
Release Date
2024-12-02
Model Name
cohere-rerank-v3.5
Total Evaluations
3300

Performance Record

Wins1350 (40.9%)
Losses1867 (56.6%)
Ties83 (2.5%)
Wins
Losses
Ties

Rerankers Are Just One Piece of RAG

Agentset gives you a managed RAG pipeline with the top-ranked models and best practices baked in. No infrastructure to maintain, no reranking to configure.

Trusted by teams building production RAG applications

5M+
Documents
1,500+
Teams
99.9%
Uptime

Performance Overview

ELO ratings by dataset

Cohere Rerank 3.5's ELO performance varies across different benchmark datasets, showing its strengths in specific domains.

Cohere Rerank 3.5 - ELO by Dataset

Detailed Metrics

Dataset breakdown

Performance metrics across different benchmark datasets, including accuracy and latency percentiles.

arguana

ELO 169247.4% WR261W-289L-0T

Accuracy Metrics

nDCG@5
0.267
nDCG@10
0.355
Recall@5
0.520
Recall@10
0.800

Latency Distribution

Mean
570ms
P50 (Median)
373ms
P90
617ms

MSMARCO

ELO 156539.5% WR217W-295L-38T

Accuracy Metrics

nDCG@5
0.000
nDCG@10
0.000
Recall@5
0.000
Recall@10
0.000

Latency Distribution

Mean
339ms
P50 (Median)
285ms
P90
304ms

DBPedia

ELO 147638.9% WR214W-306L-30T

Accuracy Metrics

nDCG@5
0.000
nDCG@10
0.000
Recall@5
0.000
Recall@10
0.000

Latency Distribution

Mean
286ms
P50 (Median)
279ms
P90
290ms

PG

ELO 145647.6% WR262W-288L-0T

Accuracy Metrics

nDCG@5
0.000
nDCG@10
0.000
Recall@5
0.000
Recall@10
0.000

Latency Distribution

Mean
458ms
P50 (Median)
360ms
P90
615ms

FiQa

ELO 128631.6% WR174W-369L-7T

Accuracy Metrics

nDCG@5
0.124
nDCG@10
0.128
Recall@5
0.123
Recall@10
0.130

Latency Distribution

Mean
364ms
P50 (Median)
315ms
P90
401ms

business reports

ELO 123340.4% WR222W-320L-8T

Accuracy Metrics

nDCG@5
0.000
nDCG@10
0.000
Recall@5
0.000
Recall@10
0.000

Latency Distribution

Mean
334ms
P50 (Median)
293ms
P90
503ms

Build RAG in Minutes, Not Months

Agentset gives you a complete RAG API with top-ranked rerankers and embedding models 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);
}

Compare Models

See how it stacks up

Compare Cohere Rerank 3.5 with other top rerankers to understand the differences in performance, accuracy, and latency.