GPT-5.4 Pro vs GPT-5.1

Detailed comparison between GPT-5.4 Pro and GPT-5.1 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

GPT-5.1 takes the lead.

Both GPT-5.4 Pro and GPT-5.1 are powerful language models designed for RAG applications. However, their performance characteristics differ in important ways.

Why GPT-5.1:

  • GPT-5.1 has 358 higher ELO rating
  • GPT-5.1 is 59.5s faster on average
  • GPT-5.1 has a 40.9% higher win rate

Overview

Key metrics

ELO Rating

Overall ranking quality

GPT-5.4 Pro

1330

GPT-5.1

1689

Win Rate

Head-to-head performance

GPT-5.4 Pro

24.6%

GPT-5.1

65.5%

Quality Score

Overall quality metric

GPT-5.4 Pro

4.94

GPT-5.1

4.97

Average Latency

Response time

GPT-5.4 Pro

75663ms

GPT-5.1

16192ms

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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

MetricGPT-5.4 ProGPT-5.1Description
Overall Performance
ELO Rating
1330
1689
Overall ranking quality based on pairwise comparisons
Win Rate
24.6%
65.5%
Percentage of comparisons won against other models
Quality Score
4.94
4.97
Average quality across all RAG metrics
Pricing & Context
Input Price per 1M
$30.00
$1.25
Cost per million input tokens
Output Price per 1M
$180.00
$10.00
Cost per million output tokens
Context Window
1050K
400K
Maximum context window size
Release Date
2026-03-05
2025-11-13
Model release date
Performance Metrics
Avg Latency
75.7s
16.2s
Average response time across all datasets

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import { Agentset } from "agentset";

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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 benchmark

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

MSMARCO

MetricGPT-5.4 ProGPT-5.1Description
Quality Metrics
Correctness
4.97
4.97
Factual accuracy of responses
Faithfulness
5.00
4.97
Adherence to source material
Grounding
5.00
4.97
Citations and context usage
Relevance
4.93
5.00
Query alignment and focus
Completeness
4.73
4.93
Coverage of all aspects
Overall
4.93
4.97
Average across all metrics
Latency Metrics
Mean
68388ms
9111ms
Average response time
Min8911ms3841msFastest response time
Max165229ms34731msSlowest response time

PG

MetricGPT-5.4 ProGPT-5.1Description
Quality Metrics
Correctness
5.00
5.00
Factual accuracy of responses
Faithfulness
5.00
5.00
Adherence to source material
Grounding
5.00
5.00
Citations and context usage
Relevance
5.00
5.00
Query alignment and focus
Completeness
4.97
4.77
Coverage of all aspects
Overall
4.99
4.95
Average across all metrics
Latency Metrics
Mean
156451ms
29008ms
Average response time
Min57901ms4393msFastest response time
Max250411ms43887msSlowest response time

SciFact

MetricGPT-5.4 ProGPT-5.1Description
Quality Metrics
Correctness
4.87
5.00
Factual accuracy of responses
Faithfulness
4.90
5.00
Adherence to source material
Grounding
4.87
5.00
Citations and context usage
Relevance
4.93
4.97
Query alignment and focus
Completeness
4.87
4.97
Coverage of all aspects
Overall
4.89
4.99
Average across all metrics
Latency Metrics
Mean
2148ms
10454ms
Average response time
Min1111ms4700msFastest response time
Max3838ms21205msSlowest response time

Explore More

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