Qwen3 Reranker 8B vs Zerank 1

Detailed comparison between Qwen3 Reranker 8B and Zerank 1. See which reranker best meets your accuracy and performance needs. If you want to compare these models on your data, try Agentset.

Model Comparison

Zerank 1 takes the lead.

Both Qwen3 Reranker 8B and Zerank 1 are powerful reranking models designed to improve retrieval quality in RAG applications. However, their performance characteristics differ in important ways.

Why Zerank 1:

  • Zerank 1 has 100 higher ELO rating
  • Zerank 1 is 4421ms faster on average
  • Zerank 1 has a 6.0% higher win rate

Overview

Key metrics

ELO Rating

Overall ranking quality

Qwen3 Reranker 8B

1473

Zerank 1

1573

Win Rate

Head-to-head performance

Qwen3 Reranker 8B

51.2%

Zerank 1

57.2%

Accuracy (nDCG@10)

Ranking quality metric

Qwen3 Reranker 8B

0.106

Zerank 1

0.082

Average Latency

Response time

Qwen3 Reranker 8B

4687ms

Zerank 1

266ms

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

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

MetricQwen3 Reranker 8BZerank 1Description
Overall Performance
ELO Rating
1473
1573
Overall ranking quality based on pairwise comparisons
Win Rate
51.2%
57.2%
Percentage of comparisons won against other models
Pricing & Availability
Price per 1M tokens
$0.050
$0.025
Cost per million tokens processed
Release Date
2025-06-06
2025-07-10
Model release date
Accuracy Metrics
Avg nDCG@10
0.106
0.082
Normalized discounted cumulative gain at position 10
Performance Metrics
Avg Latency
4687ms
266ms
Average response time across all datasets

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);
}

Dataset Performance

By field

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

MSMARCO

MetricQwen3 Reranker 8BZerank 1Description
Latency Metrics
Mean
1728ms
232ms
Average response time
P50
1624ms
226ms
50th percentile (median)
P90
1679ms
245ms
90th percentile

arguana

MetricQwen3 Reranker 8BZerank 1Description
Accuracy Metrics
nDCG@5
0.492
0.308
Ranking quality at top 5 results
nDCG@10
0.519
0.369
Ranking quality at top 10 results
Recall@5
0.800
0.580
% of relevant docs in top 5
Recall@10
0.880
0.760
% of relevant docs in top 10
Latency Metrics
Mean
13109ms
287ms
Average response time
P50
2812ms
275ms
50th percentile (median)
P90
3425ms
332ms
90th percentile

FiQa

MetricQwen3 Reranker 8BZerank 1Description
Accuracy Metrics
nDCG@5
0.114
0.115
Ranking quality at top 5 results
nDCG@10
0.118
0.121
Ranking quality at top 10 results
Recall@5
0.105
0.105
% of relevant docs in top 5
Recall@10
0.110
0.125
% of relevant docs in top 10
Latency Metrics
Mean
7242ms
259ms
Average response time
P50
2278ms
258ms
50th percentile (median)
P90
2890ms
276ms
90th percentile

business reports

MetricQwen3 Reranker 8BZerank 1Description
Latency Metrics
Mean
1803ms
289ms
Average response time
P50
1763ms
272ms
50th percentile (median)
P90
2097ms
363ms
90th percentile

PG

MetricQwen3 Reranker 8BZerank 1Description
Latency Metrics
Mean
2567ms
293ms
Average response time
P50
2579ms
279ms
50th percentile (median)
P90
2634ms
348ms
90th percentile

DBPedia

MetricQwen3 Reranker 8BZerank 1Description
Latency Metrics
Mean
1673ms
238ms
Average response time
P50
1673ms
233ms
50th percentile (median)
P90
1787ms
257ms
90th percentile

Explore More

Compare more rerankers

See how all reranking models stack up. Compare Cohere, Jina AI, Voyage, ZeRank, and more. View comprehensive benchmarks, compare performance metrics, and find the perfect reranker for your RAG application.