# Grok 4.7 vs o3-pro

> Grok 4.7 is the stronger model overall, scoring 46.6 to 42.7 on the Noometry Index.

- Canonical page: https://noometry.com/compare/grok-4-7-vs-o3-pro
- Last updated: 2026-10-10
- Shared benchmarks: 0

## Summary

- The widest gap is in long context, where o3-pro leads 72.1 to 43.2.
- Grok 4.7 is cheaper at $2 / $6 per million input/output tokens, against $20 / $80 for o3-pro.
- Grok 4.7 accepts more context: 500K tokens versus 200K.

## Snapshot

| | Grok 4.7 | o3-pro |
|---|---|---|
| Provider | xAI | OpenAI |
| Noometry Index | 46.6 | 42.7 |
| Rank | 56 | 94 |
| Context | 500K | 200K |
| Input $/M | $2 | $20 |
| Output $/M | $6 | $80 |
| Weights | Proprietary | Proprietary |

## Coding

- Grok 4.7: 55.0 (#23)
- o3-pro: 55.1 (#22)

| Benchmark | Grok 4.7 | o3-pro |
|---|---|---|
| Aider Polyglot | — | 84.9% |
| CursorBench | 46.3% | — |
| LMArena WebDev | 1636 | — |
| FrontierSWE | 29.5% | — |
| SciCode | 57.4% | — |
| WeirdML | — | 58.2% |
| LMArena Coding | 1423 | — |

## Reasoning

- Grok 4.7: 40.1 (#49)
- o3-pro: 24.1 (#152)

| Benchmark | Grok 4.7 | o3-pro |
|---|---|---|
| ARC-AGI-2 | — | 4.9% |
| Kagi LLM Benchmark | — | 72.1% |
| NYT Connections (extended) | 76.8% | — |
| ARC-AGI-1 | — | 59.3% |
| CritPt | 17.7% | — |
| LMArena Hard Prompts | 1409 | — |
| DTBench | — | 86.9% |
| LMCA | — | 38.5% |
| Epoch Capabilities Index | — | 147.43 |

## Math

- Grok 4.7: 41.1 (#73)
- o3-pro: —

| Benchmark | Grok 4.7 | o3-pro |
|---|---|---|
| ProofBench | 34% | — |
| LMArena Math | 1393 | — |

## Knowledge

- Grok 4.7: 38.7 (#130)
- o3-pro: 29.0 (#234)

| Benchmark | Grok 4.7 | o3-pro |
|---|---|---|
| Confabulations | — | 14.2% |
| Vectara Hallucination Rate | — | 23.3% |
| LMArena Expert | 1413 | — |

## Multimodal

- Grok 4.7: 28.8 (#107)
- o3-pro: —

| Benchmark | Grok 4.7 | o3-pro |
|---|---|---|
| Furniture Assembly | 20.8% | — |

## Multilingual

- Grok 4.7: 51.2 (#108)
- o3-pro: —

| Benchmark | Grok 4.7 | o3-pro |
|---|---|---|
| LMArena Non-English | 1392 | — |
| LMArena Chinese | 1476 | — |
| LMArena Russian | 1396 | — |

## Instruction Following

- Grok 4.7: 74.3 (#98)
- o3-pro: —

| Benchmark | Grok 4.7 | o3-pro |
|---|---|---|
| LMArena Instruction Following | 1406 | — |

## Long Context

- Grok 4.7: 43.2 (#97)
- o3-pro: 72.1 (#1)

| Benchmark | Grok 4.7 | o3-pro |
|---|---|---|
| Fiction.LiveBench | — | 97.2% |
| LMArena Longer Query | 1416 | — |

## Writing & Preference

- Grok 4.7: 70.1 (#23)
- o3-pro: 57.1 (#128)

| Benchmark | Grok 4.7 | o3-pro |
|---|---|---|
| LMArena Text | 1397 | — |
| LMArena Creative Writing | 1391 | — |
| Short-Story Creative Writing | — | 84.4% |
| EQ-Bench Creative Writing | 2007 | — |
| LMArena Multi-Turn | 1389 | — |

## FAQ

### Is Grok 4.7 better than o3-pro?

Grok 4.7 is the stronger model overall, scoring 46.6 to 42.7 on the Noometry Index.

### Which is cheaper, Grok 4.7 or o3-pro?

Grok 4.7 is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; o3-pro lists at $20 and $80.

### Is Grok 4.7 or o3-pro better for coding?

They score almost the same on coding (55.0 vs 55.1); test both on your own repository before choosing.

### Which has the bigger context window?

Grok 4.7 does, with 500K tokens against 200K.

### How many benchmarks do Grok 4.7 and o3-pro share?

0 benchmarks have published results for both models. Grok 4.7 has 21 scored results on Noometry and o3-pro has 12.