Contextual AI Rerank v2 Instruct vs Zerank 1 Small
Detailed comparison between Contextual AI Rerank v2 Instruct and Zerank 1 Small. 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 Small takes the lead.
Both Contextual AI Rerank v2 Instruct and Zerank 1 Small are powerful reranking models designed to improve retrieval quality in RAG applications. However, their performance characteristics differ in important ways.
Why Zerank 1 Small:
- Zerank 1 Small has 69 higher ELO rating
- Zerank 1 Small is 3086ms faster on average
- Zerank 1 Small has a 12.7% higher win rate
Overview
Key metrics
ELO Rating
Overall ranking quality
Contextual AI Rerank v2 Instruct
Zerank 1 Small
Win Rate
Head-to-head performance
Contextual AI Rerank v2 Instruct
Zerank 1 Small
Accuracy (nDCG@10)
Ranking quality metric
Contextual AI Rerank v2 Instruct
Zerank 1 Small
Average Latency
Response time
Contextual AI Rerank v2 Instruct
Zerank 1 Small
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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
| Metric | Contextual AI Rerank v2 Instruct | Zerank 1 Small | Description |
|---|---|---|---|
| Overall Performance | |||
| ELO Rating | 1469 | 1539 | Overall ranking quality based on pairwise comparisons |
| Win Rate | 42.3% | 55.0% | Percentage of comparisons won against other models |
| Pricing & Availability | |||
| Price per 1M tokens | $0.050 | $0.025 | Cost per million tokens processed |
| Release Date | 2025-09-12 | 2025-07-10 | Model release date |
| Accuracy Metrics | |||
| Avg nDCG@10 | 0.114 | 0.083 | Normalized discounted cumulative gain at position 10 |
| Performance Metrics | |||
| Avg Latency | 3333ms | 248ms | 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
| Metric | Contextual AI Rerank v2 Instruct | Zerank 1 Small | Description |
|---|---|---|---|
| Latency Metrics | |||
| Mean | 3283ms | 217ms | Average response time |
| P50 | 3260ms | 214ms | 50th percentile (median) |
| P90 | 3885ms | 227ms | 90th percentile |
arguana
| Metric | Contextual AI Rerank v2 Instruct | Zerank 1 Small | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.525 | 0.279 | Ranking quality at top 5 results |
| nDCG@10 | 0.560 | 0.375 | Ranking quality at top 10 results |
| Recall@5 | 0.860 | 0.520 | % of relevant docs in top 5 |
| Recall@10 | 0.960 | 0.820 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 3627ms | 256ms | Average response time |
| P50 | 3601ms | 254ms | 50th percentile (median) |
| P90 | 4037ms | 280ms | 90th percentile |
FiQa
| Metric | Contextual AI Rerank v2 Instruct | Zerank 1 Small | Description |
|---|---|---|---|
| Accuracy Metrics | |||
| nDCG@5 | 0.119 | 0.114 | Ranking quality at top 5 results |
| nDCG@10 | 0.125 | 0.124 | Ranking quality at top 10 results |
| Recall@5 | 0.123 | 0.098 | % of relevant docs in top 5 |
| Recall@10 | 0.135 | 0.125 | % of relevant docs in top 10 |
| Latency Metrics | |||
| Mean | 3283ms | 248ms | Average response time |
| P50 | 3209ms | 244ms | 50th percentile (median) |
| P90 | 3891ms | 266ms | 90th percentile |
business reports
| Metric | Contextual AI Rerank v2 Instruct | Zerank 1 Small | Description |
|---|---|---|---|
| Latency Metrics | |||
| Mean | 3231ms | 251ms | Average response time |
| P50 | 3129ms | 242ms | 50th percentile (median) |
| P90 | 3651ms | 298ms | 90th percentile |
PG
| Metric | Contextual AI Rerank v2 Instruct | Zerank 1 Small | Description |
|---|---|---|---|
| Latency Metrics | |||
| Mean | 3566ms | 287ms | Average response time |
| P50 | 3475ms | 274ms | 50th percentile (median) |
| P90 | 4148ms | 345ms | 90th percentile |
DBPedia
| Metric | Contextual AI Rerank v2 Instruct | Zerank 1 Small | Description |
|---|---|---|---|
| Latency Metrics | |||
| Mean | 3010ms | 226ms | Average response time |
| P50 | 3042ms | 223ms | 50th percentile (median) |
| P90 | 3283ms | 241ms | 90th percentile |
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