Claude Opus 4.6 vs Grok 4 Fast
Detailed comparison between Claude Opus 4.6 and Grok 4 Fast for RAG applications. See which LLM best meets your accuracy, performance, and cost needs.
Model Comparison
Claude Opus 4.6 takes the lead.
Both Claude Opus 4.6 and Grok 4 Fast are powerful language models designed for RAG applications. However, their performance characteristics differ in important ways.
Why Claude Opus 4.6:
- Claude Opus 4.6 has 164 higher ELO rating
- Claude Opus 4.6 has a 20.4% higher win rate
Overview
Key metrics
ELO Rating
Overall ranking quality
Claude Opus 4.6
Grok 4 Fast
Win Rate
Head-to-head performance
Claude Opus 4.6
Grok 4 Fast
Quality Score
Overall quality metric
Claude Opus 4.6
Grok 4 Fast
Average Latency
Response time
Claude Opus 4.6
Grok 4 Fast
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 4.6 | Grok 4 Fast | Description |
|---|---|---|---|
| Overall Performance | |||
| ELO Rating | 1780 | 1616 | Overall ranking quality based on pairwise comparisons |
| Win Rate | 74.8% | 54.3% | Percentage of comparisons won against other models |
| Quality Score | 4.88 | 4.99 | Average quality across all RAG metrics |
| Pricing & Context | |||
| Input Price per 1M | $5.00 | $0.20 | Cost per million input tokens |
| Output Price per 1M | $25.00 | $0.50 | Cost per million output tokens |
| Context Window | 1000K | 2000K | Maximum context window size |
| Release Date | 2026-02-05 | 2025-09-19 | Model release date |
| Performance Metrics | |||
| Avg Latency | 11.5s | 5.9s | 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 4.6 | Grok 4 Fast | Description |
|---|---|---|---|
| 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 | 5.00 | 5.00 | Coverage of all aspects |
| Overall | 5.00 | 5.00 | Average across all metrics |
| Latency Metrics | |||
| Mean | 7669ms | 3894ms | Average response time |
| Min | 3748ms | 1742ms | Fastest response time |
| Max | 12462ms | 6649ms | Slowest response time |
PG
| Metric | Claude Opus 4.6 | Grok 4 Fast | Description |
|---|---|---|---|
| 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 | 5.00 | 4.94 | Coverage of all aspects |
| Overall | 5.00 | 4.99 | Average across all metrics |
| Latency Metrics | |||
| Mean | 16812ms | 9142ms | Average response time |
| Min | 11207ms | 4767ms | Fastest response time |
| Max | 26006ms | 17055ms | Slowest response time |
SciFact
| Metric | Claude Opus 4.6 | Grok 4 Fast | Description |
|---|---|---|---|
| Quality Metrics | |||
| Correctness | 4.55 | 5.00 | Factual accuracy of responses |
| Faithfulness | 4.64 | 5.00 | Adherence to source material |
| Grounding | 4.64 | 5.00 | Citations and context usage |
| Relevance | 5.00 | 5.00 | Query alignment and focus |
| Completeness | 4.36 | 4.91 | Coverage of all aspects |
| Overall | 4.64 | 4.98 | Average across all metrics |
| Latency Metrics | |||
| Mean | 10159ms | 4516ms | Average response time |
| Min | 4747ms | 2358ms | Fastest response time |
| Max | 19093ms | 14942ms | 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.