Gemini 3 Pro Preview vs GPT-5.2

Detailed comparison between Gemini 3 Pro Preview and GPT-5.2 for RAG applications. See which LLM best meets your accuracy, performance, and cost needs. If you want to compare these models on your data, try Agentset.

Model Comparison

Two competitive LLMs, closely matched.

Both Gemini 3 Pro Preview and GPT-5.2 are powerful language models designed for RAG applications. They show comparable performance across key metrics.

Key similarities:

  • Gemini 3 Pro Preview has 18 higher ELO rating
  • GPT-5.2 delivers better overall quality (4.97 vs 4.90)
  • GPT-5.2 is 12.5s faster on average

Overview

Key metrics

ELO Rating

Overall ranking quality

Gemini 3 Pro Preview

1509

GPT-5.2

1491

Win Rate

Head-to-head performance

Gemini 3 Pro Preview

44.1%

GPT-5.2

40.1%

Quality Score

Overall quality metric

Gemini 3 Pro Preview

4.90

GPT-5.2

4.97

Average Latency

Response time

Gemini 3 Pro Preview

17904ms

GPT-5.2

5380ms

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Visual Performance Analysis

Performance

ELO Rating Comparison

Win/Loss/Tie Breakdown

Quality Across Datasets (Overall Score)

Latency Distribution (ms)

Breakdown

How the models stack up

MetricGemini 3 Pro PreviewGPT-5.2Description
Overall Performance
ELO Rating
1509
1491
Overall ranking quality based on pairwise comparisons
Win Rate
44.1%
40.1%
Percentage of comparisons won against other models
Quality Score
4.90
4.97
Average quality across all RAG metrics
Pricing & Context
Input Price per 1M
$2.00
$1.75
Cost per million input tokens
Output Price per 1M
$12.00
$14.00
Cost per million output tokens
Context Window
1049K
400K
Maximum context window size
Release Date
2025-11-18
2025-12-11
Model release date
Performance Metrics
Avg Latency
17.9s
5.4s
Average response time across all datasets

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}

Dataset Performance

By benchmark

Comprehensive comparison of RAG quality metrics (correctness, faithfulness, grounding, relevance, completeness) and latency for each benchmark dataset.

MSMARCO

MetricGemini 3 Pro PreviewGPT-5.2Description
Quality Metrics
Correctness
4.83
5.00
Factual accuracy of responses
Faithfulness
4.83
5.00
Adherence to source material
Grounding
4.83
5.00
Citations and context usage
Relevance
5.00
4.97
Query alignment and focus
Completeness
4.90
4.83
Coverage of all aspects
Overall
4.88
4.96
Average across all metrics
Latency Metrics
Mean
13990ms
2652ms
Average response time
Min7461ms796msFastest response time
Max26343ms5810msSlowest response time

PG

MetricGemini 3 Pro PreviewGPT-5.2Description
Quality Metrics
Correctness
4.90
5.00
Factual accuracy of responses
Faithfulness
4.93
5.00
Adherence to source material
Grounding
4.93
5.00
Citations and context usage
Relevance
5.00
4.97
Query alignment and focus
Completeness
4.73
4.97
Coverage of all aspects
Overall
4.90
4.99
Average across all metrics
Latency Metrics
Mean
25137ms
8702ms
Average response time
Min13317ms2755msFastest response time
Max62299ms14361msSlowest response time

SciFact

MetricGemini 3 Pro PreviewGPT-5.2Description
Quality Metrics
Correctness
4.93
4.93
Factual accuracy of responses
Faithfulness
4.97
5.00
Adherence to source material
Grounding
4.97
5.00
Citations and context usage
Relevance
4.97
5.00
Query alignment and focus
Completeness
4.83
4.80
Coverage of all aspects
Overall
4.93
4.95
Average across all metrics
Latency Metrics
Mean
14583ms
4785ms
Average response time
Min10135ms1318msFastest response time
Max21489ms10172msSlowest response time

Explore More

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