GPT-OSS 120B vs Grok 4 Fast
Detailed comparison between GPT-OSS 120B and Grok 4 Fast for RAG applications. See which LLM best meets your accuracy, performance, and cost needs.
Model Comparison
Grok 4 Fast takes the lead.
Both GPT-OSS 120B and Grok 4 Fast are powerful language models designed for RAG applications. However, their performance characteristics differ in important ways.
Why Grok 4 Fast:
- Grok 4 Fast has 343 higher ELO rating
- Grok 4 Fast delivers better overall quality (4.96 vs 4.85)
- Grok 4 Fast is 5.3s faster on average
- Grok 4 Fast has a 40.4% higher win rate
Overview
Key metrics
ELO Rating
Overall ranking quality
GPT-OSS 120B
Grok 4 Fast
Win Rate
Head-to-head performance
GPT-OSS 120B
Grok 4 Fast
Quality Score
Overall quality metric
GPT-OSS 120B
Grok 4 Fast
Average Latency
Response time
GPT-OSS 120B
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 | GPT-OSS 120B | Grok 4 Fast | Description |
|---|---|---|---|
| Overall Performance | |||
| ELO Rating | 1303 | 1645 | Overall ranking quality based on pairwise comparisons |
| Win Rate | 17.9% | 58.3% | Percentage of comparisons won against other models |
| Quality Score | 4.85 | 4.96 | Average quality across all RAG metrics |
| Pricing & Context | |||
| Input Price per 1M | $0.04 | $0.20 | Cost per million input tokens |
| Output Price per 1M | $0.19 | $0.50 | Cost per million output tokens |
| Context Window | 131K | 2000K | Maximum context window size |
| Release Date | 2025-08-05 | 2025-09-19 | Model release date |
| Performance Metrics | |||
| Avg Latency | 11.2s | 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 | GPT-OSS 120B | Grok 4 Fast | Description |
|---|---|---|---|
| Quality Metrics | |||
| Correctness | 4.93 | 4.90 | Factual accuracy of responses |
| Faithfulness | 4.90 | 4.90 | Adherence to source material |
| Grounding | 4.90 | 4.90 | Citations and context usage |
| Relevance | 4.97 | 5.00 | Query alignment and focus |
| Completeness | 4.80 | 4.90 | Coverage of all aspects |
| Overall | 4.90 | 4.92 | Average across all metrics |
| Latency Metrics | |||
| Mean | 5616ms | 3894ms | Average response time |
| Min | 1255ms | 1742ms | Fastest response time |
| Max | 20330ms | 6649ms | Slowest response time |
PG
| Metric | GPT-OSS 120B | Grok 4 Fast | Description |
|---|---|---|---|
| Quality Metrics | |||
| Correctness | 4.87 | 5.00 | Factual accuracy of responses |
| Faithfulness | 4.87 | 5.00 | Adherence to source material |
| Grounding | 4.87 | 5.00 | Citations and context usage |
| Relevance | 4.90 | 5.00 | Query alignment and focus |
| Completeness | 4.83 | 4.97 | Coverage of all aspects |
| Overall | 4.87 | 4.99 | Average across all metrics |
| Latency Metrics | |||
| Mean | 19128ms | 9142ms | Average response time |
| Min | 1317ms | 4767ms | Fastest response time |
| Max | 69491ms | 17055ms | Slowest response time |
SciFact
| Metric | GPT-OSS 120B | Grok 4 Fast | Description |
|---|---|---|---|
| Quality Metrics | |||
| Correctness | 4.80 | 5.00 | Factual accuracy of responses |
| Faithfulness | 4.87 | 5.00 | Adherence to source material |
| Grounding | 4.87 | 5.00 | Citations and context usage |
| Relevance | 4.77 | 5.00 | Query alignment and focus |
| Completeness | 4.67 | 4.83 | Coverage of all aspects |
| Overall | 4.79 | 4.97 | Average across all metrics |
| Latency Metrics | |||
| Mean | 8854ms | 4516ms | Average response time |
| Min | 0ms | 2358ms | Fastest response time |
| Max | 35709ms | 14942ms | Slowest response time |
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