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Gemini Embedding 2 vs Gemini text-embedding-004

Detailed comparison between Gemini Embedding 2 and Gemini text-embedding-004. See which embedding best meets your accuracy and performance needs. If you want to compare these models on your data, try Agentset.

Explore Gemini Embedding 2Explore Gemini text-embedding-004

Model Comparison

Gemini Embedding 2 takes the lead.

Both Gemini Embedding 2 and Gemini text-embedding-004 are powerful embedding models designed to improve retrieval quality in RAG applications. However, their performance characteristics differ in important ways.

Why Gemini Embedding 2:

  • Gemini Embedding 2 has 239 higher ELO rating
  • Gemini Embedding 2 delivers better accuracy (nDCG@10: 0.628 vs 0.538)
  • Gemini text-embedding-004 is 419ms faster on average
  • Gemini Embedding 2 has a 31.1% higher win rate

Overview

Key metrics

ELO Rating

Overall ranking quality

Gemini Embedding 2

1605

Gemini text-embedding-004

1366

Win Rate

Head-to-head performance

Gemini Embedding 2

59.5%

Gemini text-embedding-004

28.4%

Accuracy (nDCG@10)

Ranking quality metric

Gemini Embedding 2

0.628

Gemini text-embedding-004

0.538

Average Latency

Response time

Gemini Embedding 2

435ms

Gemini text-embedding-004

16ms

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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

MetricGemini Embedding 2Gemini text-embedding-004Description
Overall Performance
ELO Rating
1605
1366
Overall ranking quality based on pairwise comparisons
Win Rate
59.5%
28.4%
Percentage of comparisons won against other models
Pricing & Availability
Price per 1M tokens
$0.000
$0.020
Cost per million tokens processed
Dimensions
3072
768
Vector embedding dimensions (lower is more efficient)
Release Date
2026-03-10
2024-05-14
Model release date
Accuracy Metrics
Avg nDCG@10
0.628
0.538
Normalized discounted cumulative gain at position 10
Performance Metrics
Avg Latency
435ms
16ms
Average response time across all datasets

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Agentset gives you a complete RAG API with top-ranked embedding models and smart retrieval built in. Upload your data, call the API, and get accurate results from day one.

Get started freeRead the docs 
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.

FiQa

MetricGemini Embedding 2Gemini text-embedding-004Description
Accuracy Metrics
nDCG@5
0.843
0.744
Ranking quality at top 5 results
nDCG@10
0.835
0.730
Ranking quality at top 10 results
Recall@5
0.763
0.647
% of relevant docs in top 5
Recall@10
0.816
0.752
% of relevant docs in top 10
Latency Metrics
Mean
466ms
16ms
Average response time
P50
454ms
16ms
50th percentile (median)
P90
605ms
16ms
90th percentile

MSMARCO

MetricGemini Embedding 2Gemini text-embedding-004Description
Accuracy Metrics
nDCG@5
0.956
0.932
Ranking quality at top 5 results
nDCG@10
0.939
0.918
Ranking quality at top 10 results
Recall@5
0.122
0.117
% of relevant docs in top 5
Recall@10
0.221
0.208
% of relevant docs in top 10
Latency Metrics
Mean
441ms
18ms
Average response time
P50
446ms
18ms
50th percentile (median)
P90
584ms
18ms
90th percentile

SciFact

MetricGemini Embedding 2Gemini text-embedding-004Description
Accuracy Metrics
nDCG@5
0.871
0.728
Ranking quality at top 5 results
nDCG@10
0.871
0.729
Ranking quality at top 10 results
Recall@5
0.959
0.813
% of relevant docs in top 5
Recall@10
0.959
0.857
% of relevant docs in top 10
Latency Metrics
Mean
404ms
15ms
Average response time
P50
360ms
15ms
50th percentile (median)
P90
537ms
15ms
90th percentile

DBPedia

MetricGemini Embedding 2Gemini text-embedding-004Description
Accuracy Metrics
nDCG@5
0.788
0.747
Ranking quality at top 5 results
nDCG@10
0.792
0.737
Ranking quality at top 10 results
Recall@5
0.061
0.057
% of relevant docs in top 5
Recall@10
0.120
0.108
% of relevant docs in top 10
Latency Metrics
Mean
436ms
14ms
Average response time
P50
432ms
14ms
50th percentile (median)
P90
592ms
14ms
90th percentile

business reports

MetricGemini Embedding 2Gemini text-embedding-004Description
Accuracy Metrics
nDCG@5
0.091
0.000
Ranking quality at top 5 results
nDCG@10
0.084
0.000
Ranking quality at top 10 results
Recall@5
0.012
0.000
% of relevant docs in top 5
Recall@10
0.020
0.000
% of relevant docs in top 10
Latency Metrics
Mean
439ms
15ms
Average response time
P50
431ms
15ms
50th percentile (median)
P90
603ms
15ms
90th percentile

ARCD

MetricGemini Embedding 2Gemini text-embedding-004Description
Accuracy Metrics
nDCG@5
0.868
0.021
Ranking quality at top 5 results
nDCG@10
0.875
0.027
Ranking quality at top 10 results
Recall@5
0.940
0.040
% of relevant docs in top 5
Recall@10
0.960
0.060
% of relevant docs in top 10
Latency Metrics
Mean
410ms
15ms
Average response time
P50
359ms
15ms
50th percentile (median)
P90
586ms
15ms
90th percentile

Explore More

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