# GPT-6 Sol vs o3-mini

> GPT-6 Sol is the stronger model overall, scoring 49.2 to 36.7 on the Noometry Index. o3-mini costs 2.1× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-6-sol-vs-o3-mini
- Last updated: 2026-10-10
- Shared benchmarks: 13

## Summary

- They share 13 benchmarks with published results for both. GPT-6 Sol scores higher in 8 categories and o3-mini in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-6 Sol leads 49.3 to 16.3.
- o3-mini is cheaper at $1.10 / $4.40 per million input/output tokens, against $2 / $10 for GPT-6 Sol.
- GPT-6 Sol accepts more context: 1.05M tokens versus 200K.

## Snapshot

| | GPT-6 Sol | o3-mini |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 49.2 | 36.7 |
| Rank | 46 | 205 |
| Context | 1.05M | 200K |
| Input $/M | $2 | $1.10 |
| Output $/M | $10 | $4.40 |
| Weights | Proprietary | Proprietary |

## Coding

- GPT-6 Sol: 59.6 (#11)
- o3-mini: 41.4 (#116)

| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| LMArena Coding | 1453 | 1378 |
| DeepSWE | 68.8% | — |
| FrontierCode | 49.3% | — |
| Aider Polyglot | — | 60.4% |
| LMArena WebDev | 1692 | — |
| SciCode | — | 39.8% |
| GSO | — | 1.3% |
| WeirdML | — | 43.7% |
| LiveBench Coding | — | 82.7% |
| CadEval | — | 54% |

## Agentic & Tool Use

- GPT-6 Sol: 33.5 (#49)
- o3-mini: 29.3 (#79)

| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| Cybench | — | 22.5% |
| GDP.pdf | 28% | — |

## Reasoning

- GPT-6 Sol: 49.3 (#34)
- o3-mini: 16.3 (#295)

| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| LMArena Hard Prompts | 1420 | 1366 |
| ARC-AGI-2 | — | 3% |
| SimpleBench | — | 22.8% |
| NYT Connections (extended) | 90.1% | — |
| ARC-AGI-1 | — | 34.5% |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 17% |
| EBR-Bench | 53.3% | — |
| LiveBench Reasoning | — | 89.6% |
| Mystery Game Puzzles | — | 7% |
| DTBench | — | 68.8% |
| LiveBench Data Analysis | — | 70.6% |
| LMCA | — | 19% |
| Epoch Capabilities Index | — | 140.35 |
| ForecastBench | — | 59.6 |
| LiveBench | — | 75.9% |

## Math

- GPT-6 Sol: 35.8 (#135)
- o3-mini: 27.6 (#236)

| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| LMArena Math | 1404 | 1396 |
| FrontierMath (Tiers 1-3) | — | 18.6% |
| FrontierMath Tier 4 | — | 0% |
| OTIS Mock AIME 2024-2025 | — | 76.9% |
| LiveBench Math | — | 77.3% |
| MATH Level 5 | — | 96.5% |
| FrontierMath (Feb 2025 set) | — | 12.4% |
| FrontierMath Tier 4 (v1) | — | 4.2% |

## Knowledge

- GPT-6 Sol: 43.0 (#87)
- o3-mini: 38.3 (#135)

| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| LMArena Expert | 1449 | 1364 |
| GPQA Diamond | — | 77% |
| SimpleQA Verified | — | 15.3% |
| Confabulations | — | 17.9% |
| Vectara Hallucination Rate | 6.5% | — |

## Multimodal

- GPT-6 Sol: 47.6 (#9)
- o3-mini: —

| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| Furniture Assembly | 58.3% | — |

## Multilingual

- GPT-6 Sol: 51.0 (#113)
- o3-mini: 45.9 (#159)

| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| LMArena Non-English | 1389 | 1319 |
| LMArena Chinese | 1416 | 1379 |
| LMArena Russian | 1407 | 1304 |
| LMArena Spanish | 1377 | 1321 |
| LMArena French | — | 1333 |
| LMArena German | — | 1303 |
| LMArena Japanese | — | 1286 |
| LMArena Korean | — | 1314 |

## Instruction Following

- GPT-6 Sol: 74.4 (#97)
- o3-mini: 75.3 (#67)

| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| LMArena Instruction Following | 1406 | 1338 |
| LiveBench Instruction Following | — | 84.4% |

## Long Context

- GPT-6 Sol: 43.2 (#100)
- o3-mini: 33.8 (#251)

| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| LMArena Longer Query | 1415 | 1343 |
| Fiction.LiveBench | — | 50% |

## Writing & Preference

- GPT-6 Sol: 72.3 (#15)
- o3-mini: 50.4 (#177)

| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| LMArena Text | 1396 | 1337 |
| LMArena Creative Writing | 1392 | 1286 |
| LMArena Multi-Turn | 1405 | 1320 |
| Short-Story Creative Writing | — | 61.7% |
| EQ-Bench Creative Writing | 2125 | — |
| LiveBench Language | — | 50.7% |

## FAQ

### Is GPT-6 Sol better than o3-mini?

GPT-6 Sol is the stronger model overall, scoring 49.2 to 36.7 on the Noometry Index. o3-mini costs 2.1× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.

### Which is cheaper, GPT-6 Sol or o3-mini?

o3-mini is cheaper. It lists at $1.10 per million input tokens and $4.40 per million output tokens; GPT-6 Sol lists at $2 and $10.

### Is GPT-6 Sol or o3-mini better for coding?

GPT-6 Sol scores higher on coding benchmarks: 59.6 versus 41.4 in the Noometry coding category.

### Which has the bigger context window?

GPT-6 Sol does, with 1.05M tokens against 200K.

### How many benchmarks do GPT-6 Sol and o3-mini share?

13 benchmarks have published results for both models. GPT-6 Sol has 22 scored results on Noometry and o3-mini has 51.