# GPT-4o mini vs o3-mini

> o3-mini is the stronger model overall, scoring 36.7 to 25.4 on the Noometry Index. GPT-4o mini costs 7.3× less per token, which makes it the better buy when o3-mini's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-4o-mini-vs-o3-mini
- Last updated: 2026-10-10
- Shared benchmarks: 40

## Summary

- They share 40 benchmarks with published results for both. GPT-4o mini scores higher in 1 category and o3-mini in 8 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where o3-mini leads 38.3 to 17.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 6.9% for GPT-4o mini and 76.9% for o3-mini.
- GPT-4o mini is cheaper at $0.15 / $0.60 per million input/output tokens, against $1.10 / $4.40 for o3-mini.
- o3-mini accepts more context: 200K tokens versus 128K.

## Snapshot

| | GPT-4o mini | o3-mini |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 25.4 | 36.7 |
| Rank | 337 | 205 |
| Context | 128K | 200K |
| Input $/M | $0.15 | $1.10 |
| Output $/M | $0.60 | $4.40 |
| Weights | Proprietary | Proprietary |

## Coding

- GPT-4o mini: 21.6 (#330)
- o3-mini: 41.4 (#116)

| Benchmark | GPT-4o mini | o3-mini |
|---|---|---|
| Aider Polyglot | 3.6% | 60.4% |
| WeirdML | 11.8% | 43.7% |
| LiveBench Coding | 43.1% | 82.7% |
| LMArena Coding | 1290 | 1378 |
| SciCode | — | 39.8% |
| GSO | — | 1.3% |
| BigCodeBench Instruct | 46.1% | — |
| BigCodeBench Complete | 57.4% | — |
| CadEval | — | 54% |
| HumanEval+ | 83.5% | — |
| MBPP+ | 72.2% | — |

## Agentic & Tool Use

- GPT-4o mini: 27.2 (#95)
- o3-mini: 29.3 (#79)

| Benchmark | GPT-4o mini | o3-mini |
|---|---|---|
| Cybench | — | 22.5% |
| BALROG | 17.4% | — |

## Reasoning

- GPT-4o mini: 8.7 (#343)
- o3-mini: 16.3 (#295)

| Benchmark | GPT-4o mini | o3-mini |
|---|---|---|
| ARC-AGI-2 | 0% | 3% |
| SimpleBench | 10.7% | 22.8% |
| Chess Puzzles | 0% | 17% |
| LiveBench Reasoning | 32.8% | 89.6% |
| LMArena Hard Prompts | 1267 | 1366 |
| Mystery Game Puzzles | 12% | 7% |
| DTBench | 54.4% | 68.8% |
| LiveBench Data Analysis | 50% | 70.6% |
| LMCA | 10.4% | 19% |
| Epoch Capabilities Index | 126.56 | 140.35 |
| LiveBench | 41.3% | 75.9% |
| Kagi LLM Benchmark | 28.8% | — |
| ARC-AGI-1 | — | 34.5% |
| CritPt | — | 0.3% |
| ForecastBench | — | 59.6 |
| PIQA | 88.7% | — |

## Math

- GPT-4o mini: 9.9 (#307)
- o3-mini: 27.6 (#236)

| Benchmark | GPT-4o mini | o3-mini |
|---|---|---|
| FrontierMath (Tiers 1-3) | 0.7% | 18.6% |
| OTIS Mock AIME 2024-2025 | 6.9% | 76.9% |
| LiveBench Math | 36.3% | 77.3% |
| LMArena Math | 1267 | 1396 |
| MATH Level 5 | 52.6% | 96.5% |
| FrontierMath Tier 4 | — | 0% |
| Omni-MATH | 28% | — |
| FrontierMath (Feb 2025 set) | — | 12.4% |
| FrontierMath Tier 4 (v1) | — | 4.2% |
| GSM8K | 91.3% | — |

## Knowledge

- GPT-4o mini: 17.7 (#279)
- o3-mini: 38.3 (#135)

| Benchmark | GPT-4o mini | o3-mini |
|---|---|---|
| GPQA Diamond | 37.7% | 77% |
| SimpleQA Verified | 8.3% | 15.3% |
| Confabulations | 37.2% | 17.9% |
| LMArena Expert | 1235 | 1364 |
| MMLU-Pro | 60.3% | — |
| GPQA (HELM) | 36.8% | — |
| BoolQ | 88.7% | — |
| MMLU | 81.8% | — |

## Multimodal

- GPT-4o mini: 25.3 (#117)
- o3-mini: —

| Benchmark | GPT-4o mini | o3-mini |
|---|---|---|
| LMArena Vision | 1066 | — |
| Video-MME | 64.8% | — |
| GeoBench | 64% | — |
| VPCT | 34% | — |

## Multilingual

- GPT-4o mini: 42.2 (#194)
- o3-mini: 45.9 (#159)

| Benchmark | GPT-4o mini | o3-mini |
|---|---|---|
| LMArena Non-English | 1266 | 1319 |
| LMArena Chinese | 1264 | 1379 |
| LMArena French | 1296 | 1333 |
| LMArena German | 1272 | 1303 |
| LMArena Japanese | 1216 | 1286 |
| LMArena Korean | 1195 | 1314 |
| LMArena Russian | 1275 | 1304 |
| LMArena Spanish | 1276 | 1321 |

## Instruction Following

- GPT-4o mini: 62.1 (#234)
- o3-mini: 75.3 (#67)

| Benchmark | GPT-4o mini | o3-mini |
|---|---|---|
| LiveBench Instruction Following | 56.8% | 84.4% |
| LMArena Instruction Following | 1259 | 1338 |
| IFEval | 78.2% | — |

## Long Context

- GPT-4o mini: 39.1 (#181)
- o3-mini: 33.8 (#251)

| Benchmark | GPT-4o mini | o3-mini |
|---|---|---|
| LMArena Longer Query | 1289 | 1343 |
| Fiction.LiveBench | — | 50% |

## Writing & Preference

- GPT-4o mini: 39.7 (#243)
- o3-mini: 50.4 (#177)

| Benchmark | GPT-4o mini | o3-mini |
|---|---|---|
| LMArena Text | 1286 | 1337 |
| LMArena Creative Writing | 1268 | 1286 |
| Short-Story Creative Writing | 67.2% | 61.7% |
| LMArena Multi-Turn | 1285 | 1320 |
| LiveBench Language | 28.6% | 50.7% |
| EQ-Bench Creative Writing | 873 | — |
| WildBench | 79.1% | — |

## FAQ

### Is GPT-4o mini better than o3-mini?

o3-mini is the stronger model overall, scoring 36.7 to 25.4 on the Noometry Index. GPT-4o mini costs 7.3× less per token, which makes it the better buy when o3-mini's lead doesn't matter for your workload.

### Which is cheaper, GPT-4o mini or o3-mini?

GPT-4o mini is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; o3-mini lists at $1.10 and $4.40.

### Is GPT-4o mini or o3-mini better for coding?

o3-mini scores higher on coding benchmarks: 41.4 versus 21.6 in the Noometry coding category.

### Which has the bigger context window?

o3-mini does, with 200K tokens against 128K.

### How many benchmarks do GPT-4o mini and o3-mini share?

40 benchmarks have published results for both models. GPT-4o mini has 60 scored results on Noometry and o3-mini has 51.