Claude Opus 4.5 vs GPT-5.1
Detailed comparison between Claude Opus 4.5 and GPT-5.1 for RAG applications. See which LLM best meets your accuracy, performance, and cost needs.
Model Comparison
GPT-5.1 takes the lead.
Both Claude Opus 4.5 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 92 higher ELO rating
- GPT-5.1 delivers better overall quality (4.98 vs 4.91)
- GPT-5.1 has a 13.2% higher win rate
Overview
Key metrics
ELO Rating
Overall ranking quality
Claude Opus 4.5
GPT-5.1
Win Rate
Head-to-head performance
Claude Opus 4.5
GPT-5.1
Quality Score
Overall quality metric
Claude Opus 4.5
GPT-5.1
Average Latency
Response time
Claude Opus 4.5
GPT-5.1
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
| Metric | Claude Opus 4.5 | GPT-5.1 | Description |
|---|---|---|---|
| Overall Performance | |||
| ELO Rating | 1619 | 1711 | Overall ranking quality based on pairwise comparisons |
| Win Rate | 56.0% | 69.3% | Percentage of comparisons won against other models |
| Quality Score | 4.91 | 4.98 | Average quality across all RAG metrics |
| Pricing & Context | |||
| Input Price per 1M | $5.00 | $1.25 | Cost per million input tokens |
| Output Price per 1M | $25.00 | $10.00 | Cost per million output tokens |
| Context Window | 200K | 400K | Maximum context window size |
| Release Date | 2025-11-24 | 2025-11-13 | Model release date |
| Performance Metrics | |||
| Avg Latency | 8.3s | 16.2s | Average response time across all datasets |
Dataset Performance
By benchmark
Comprehensive comparison of RAG quality metrics (correctness, faithfulness, grounding, relevance, completeness) and latency for each benchmark dataset.
MSMARCO
| Metric | Claude Opus 4.5 | GPT-5.1 | Description |
|---|---|---|---|
| Quality Metrics | |||
| Correctness | 4.97 | 5.00 | 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 | 4.97 | 4.93 | Coverage of all aspects |
| Overall | 4.97 | 4.99 | Average across all metrics |
| Latency Metrics | |||
| Mean | 5992ms | 9111ms | Average response time |
| Min | 2590ms | 3841ms | Fastest response time |
| Max | 8072ms | 34731ms | Slowest response time |
PG
| Metric | Claude Opus 4.5 | GPT-5.1 | Description |
|---|---|---|---|
| Quality Metrics | |||
| Correctness | 4.93 | 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 | 4.93 | 5.00 | Query alignment and focus |
| Completeness | 4.80 | 4.73 | Coverage of all aspects |
| Overall | 4.91 | 4.95 | Average across all metrics |
| Latency Metrics | |||
| Mean | 11489ms | 29008ms | Average response time |
| Min | 7945ms | 4393ms | Fastest response time |
| Max | 15934ms | 43887ms | Slowest response time |
SciFact
| Metric | Claude Opus 4.5 | GPT-5.1 | Description |
|---|---|---|---|
| Quality Metrics | |||
| Correctness | 4.73 | 5.00 | Factual accuracy of responses |
| Faithfulness | 4.80 | 5.00 | Adherence to source material |
| Grounding | 4.80 | 5.00 | Citations and context usage |
| Relevance | 4.97 | 5.00 | Query alignment and focus |
| Completeness | 4.70 | 4.97 | Coverage of all aspects |
| Overall | 4.80 | 4.99 | Average across all metrics |
| Latency Metrics | |||
| Mean | 7276ms | 10454ms | Average response time |
| Min | 4210ms | 4700ms | Fastest response time |
| Max | 10496ms | 21205ms | Slowest response time |
Explore More
Compare more LLMs
See how all LLMs stack up for RAG applications. Compare GPT-5, Claude, Gemini, and more. View comprehensive benchmarks and find the perfect LLM for your needs.