GPT-5.1 vs Grok 4 Turbo: which model should you choose?
We compared GPT-5.1 and Grok 4 Turbo on price, context window and 12 benchmarks. Grok 4 Turbo has the stronger average benchmark score; GPT-5.1 is cheaper on a blended 3:1 basis.
GPT-5.1
GPT-5.1 is a frontier model from OpenAI. It offers a 2,000,000-token context window, costs $19.01 per million input tokens and $69.84 per million output tokens, and averages 86.0 across the index's benchmark suite.
- Input
- $19.01 / 1M
- Output
- $69.84 / 1M
- Context
- 2,000,000
- Avg score
- 86.0
- Open weights
- No
Grok 4 Turbo
Grok 4 Turbo is a frontier model from xAI. It offers a 1,000,000-token context window, costs $19.21 per million input tokens and $87.37 per million output tokens, and averages 86.7 across the index's benchmark suite.
- Input
- $19.21 / 1M
- Output
- $87.37 / 1M
- Context
- 1,000,000
- Avg score
- 86.7
- Open weights
- No
Specification comparison
| Spec | GPT-5.1 | Grok 4 Turbo | Edge |
|---|---|---|---|
| Input price / 1M | $19.01 | $19.21 | A |
| Output price / 1M | $69.84 | $87.37 | A |
| Context window | 2,000,000 | 1,000,000 | A |
| Max output | 128,000 | 65,536 | A |
| Average score | 86.0 | 86.7 | B |
| Arena Elo | 1462.5 | 1466.9 | B |
| Open weights | No | No | Tie |
Benchmark comparison
GPT-5.1 wins 4, Grok 4 Turbo wins 7, and 1 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | GPT-5.1 | Grok 4 Turbo | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 86.1 | 86.1 | 0.0 | Tie |
| GPQA Diamond | 82.3 | 84.5 | 2.2 | Grok 4 Turbo |
| SWE-bench Verified | 76.1 | 73.8 | 2.3 | GPT-5.1 |
| HumanEval | 90.6 | 92.9 | 2.3 | Grok 4 Turbo |
| MATH-500 | 90.5 | 92.1 | 1.6 | Grok 4 Turbo |
| AIME 2025 | 85.6 | 85.2 | 0.4 | GPT-5.1 |
| LiveCodeBench | 78.9 | 84.7 | 5.8 | Grok 4 Turbo |
| IFEval | 90.9 | 91.1 | 0.2 | Grok 4 Turbo |
| TruthfulQA | 89.2 | 88.8 | 0.4 | GPT-5.1 |
| HellaSwag | 92.2 | 92.5 | 0.3 | Grok 4 Turbo |
| MMMU | 83.3 | 81.7 | 1.6 | GPT-5.1 |
| Arena Elo | 1462.5 | 1466.9 | 4.4 | Grok 4 Turbo |
Price analysis
On a blended 3:1 input-to-output basis, GPT-5.1 costs about $31.72 per million tokens and Grok 4 Turbo costs about $36.25. GPT-5.1 is roughly 13% cheaper than Grok 4 Turbo. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
GPT-5.1 has the larger context window at 2,000,000 tokens, compared with 1,000,000 for Grok 4 Turbo. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, GPT-5.1 wins 4, Grok 4 Turbo wins 7, and 1 are tied. On the index average, Grok 4 Turbo leads GPT-5.1 by 0.7 points (86.7 versus 86.0).
The price picture favours GPT-5.1. The context picture favours GPT-5.1. Those two dimensions often matter more than a few benchmark points once a model is good enough for the task.
If you need a single default, start with Grok 4 Turbo for quality-sensitive work and GPT-5.1 for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose GPT-5.1 if
- Unit cost matters and you want the cheaper blended price.
- You need the larger 2,000,000-token context window.
- You need the larger 128,000-token output limit.
Choose Grok 4 Turbo if
- You want the higher average benchmark score in this index.
FAQ
Is GPT-5.1 better than Grok 4 Turbo?
On the index average, Grok 4 Turbo leads GPT-5.1 by 0.7 points (86.7 versus 86.0). The better choice depends on price, context and your task. GPT-5.1 wins 4 benchmarks, Grok 4 Turbo wins 7.
Which is cheaper, GPT-5.1 or Grok 4 Turbo?
GPT-5.1 is cheaper on a blended 3:1 basis at about $31.72 per million tokens, versus $36.25 for Grok 4 Turbo.
Which has the larger context window?
GPT-5.1 has the larger context window at 2,000,000 tokens. Grok 4 Turbo has 1,000,000 tokens.
Are these models open weights?
GPT-5.1 is proprietary; Grok 4 Turbo is proprietary.
Which should I choose for production?
If you need a single default, start with Grok 4 Turbo for quality-sensitive work and GPT-5.1 for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.