Grok 4 Pro vs o4 Turbo: which model should you choose?
We compared Grok 4 Pro and o4 Turbo on price, context window and 12 benchmarks. o4 Turbo has the stronger average benchmark score; Grok 4 Pro is cheaper on a blended 3:1 basis.
Grok 4 Pro
Grok 4 Pro is a frontier model from xAI. It offers a 1,000,000-token context window, costs $19.00 per million input tokens and $77.72 per million output tokens, and averages 85.4 across the index's benchmark suite.
- Input
- $19.00 / 1M
- Output
- $77.72 / 1M
- Context
- 1,000,000
- Avg score
- 85.4
- Open weights
- No
o4 Turbo
o4 Turbo is a frontier model from OpenAI. It offers a 2,000,000-token context window, costs $19.34 per million input tokens and $82.19 per million output tokens, and averages 86.6 across the index's benchmark suite.
- Input
- $19.34 / 1M
- Output
- $82.19 / 1M
- Context
- 2,000,000
- Avg score
- 86.6
- Open weights
- No
Specification comparison
| Spec | Grok 4 Pro | o4 Turbo | Edge |
|---|---|---|---|
| Input price / 1M | $19.00 | $19.34 | A |
| Output price / 1M | $77.72 | $82.19 | A |
| Context window | 1,000,000 | 2,000,000 | B |
| Max output | 128,000 | 8,192 | A |
| Average score | 85.4 | 86.6 | B |
| Arena Elo | 1487.5 | 1468.1 | A |
| Open weights | No | No | Tie |
Benchmark comparison
Grok 4 Pro wins 4, o4 Turbo wins 8, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Grok 4 Pro | o4 Turbo | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 84.9 | 88.1 | 3.2 | o4 Turbo |
| GPQA Diamond | 79.2 | 84.8 | 5.6 | o4 Turbo |
| SWE-bench Verified | 74.7 | 78.4 | 3.7 | o4 Turbo |
| HumanEval | 89.7 | 91.0 | 1.3 | o4 Turbo |
| MATH-500 | 92.3 | 91.7 | 0.6 | Grok 4 Pro |
| AIME 2025 | 85.4 | 85.9 | 0.5 | o4 Turbo |
| LiveCodeBench | 77.8 | 80.1 | 2.3 | o4 Turbo |
| IFEval | 91.3 | 92.6 | 1.3 | o4 Turbo |
| TruthfulQA | 86.0 | 88.8 | 2.8 | o4 Turbo |
| HellaSwag | 92.8 | 91.3 | 1.5 | Grok 4 Pro |
| MMMU | 84.9 | 79.6 | 5.3 | Grok 4 Pro |
| Arena Elo | 1487.5 | 1468.1 | 19.4 | Grok 4 Pro |
Price analysis
On a blended 3:1 input-to-output basis, Grok 4 Pro costs about $33.68 per million tokens and o4 Turbo costs about $35.05. Grok 4 Pro is roughly 4% cheaper than o4 Turbo. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
o4 Turbo has the larger context window at 2,000,000 tokens, compared with 1,000,000 for Grok 4 Pro. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, Grok 4 Pro wins 4, o4 Turbo wins 8, and 0 are tied. On the index average, o4 Turbo leads Grok 4 Pro by 1.2 points (86.6 versus 85.4).
The price picture favours Grok 4 Pro. The context picture favours o4 Turbo. 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 o4 Turbo for quality-sensitive work and Grok 4 Pro for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose Grok 4 Pro if
- Unit cost matters and you want the cheaper blended price.
- You need the larger 128,000-token output limit.
Choose o4 Turbo if
- You want the higher average benchmark score in this index.
- You need the larger 2,000,000-token context window.
FAQ
Is Grok 4 Pro better than o4 Turbo?
On the index average, o4 Turbo leads Grok 4 Pro by 1.2 points (86.6 versus 85.4). The better choice depends on price, context and your task. Grok 4 Pro wins 4 benchmarks, o4 Turbo wins 8.
Which is cheaper, Grok 4 Pro or o4 Turbo?
Grok 4 Pro is cheaper on a blended 3:1 basis at about $33.68 per million tokens, versus $35.05 for o4 Turbo.
Which has the larger context window?
o4 Turbo has the larger context window at 2,000,000 tokens. Grok 4 Pro has 1,000,000 tokens.
Are these models open weights?
Grok 4 Pro is proprietary; o4 Turbo is proprietary.
Which should I choose for production?
If you need a single default, start with o4 Turbo for quality-sensitive work and Grok 4 Pro for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.