# GPT-5.3 Codex vs o3-mini

> GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 36.7 on the Noometry Index. o3-mini costs 2.5× less per token, which makes it the better buy when GPT-5.3 Codex's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-5-3-codex-vs-o3-mini
- Last updated: 2026-10-10
- Shared benchmarks: 2

## Summary

- They share 2 benchmarks with published results for both. GPT-5.3 Codex scores higher in 2 categories and o3-mini in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where GPT-5.3 Codex leads 48.0 to 29.6.
- The biggest single-benchmark swing is WeirdML: 79.3% for GPT-5.3 Codex and 43.7% for o3-mini.
- o3-mini is cheaper at $1.10 / $4.40 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- GPT-5.3 Codex accepts more context: 400K tokens versus 200K.

## Snapshot

| | GPT-5.3 Codex | o3-mini |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 45.8 | 36.7 |
| Rank | 69 | 212 |
| Context | 400K | 200K |
| Input $/M | $1.75 | $1.10 |
| Output $/M | $14 | $4.40 |
| Weights | Proprietary | Proprietary |

## Coding

- GPT-5.3 Codex: 48.6 (#56)
- o3-mini: 40.8 (#132)

| Benchmark | GPT-5.3 Codex | o3-mini |
|---|---|---|
| WeirdML | 79.3% | 43.7% |
| SWE-bench Verified | 74.8% | — |
| Aider Polyglot | — | 60.4% |
| LMArena WebDev | 1409 | — |
| SciCode | — | 39.8% |
| GSO | — | 1.3% |
| LiveBench Coding | — | 82.7% |
| LMArena Coding | — | 1378 |
| CadEval | — | 54% |
| ALE-Bench | 1,655 | — |

## Agentic & Tool Use

- GPT-5.3 Codex: 48.0 (#9)
- o3-mini: 29.6 (#84)

| Benchmark | GPT-5.3 Codex | o3-mini |
|---|---|---|
| Terminal-Bench | 78.4% | — |
| Cybench | — | 22.5% |
| METR Time Horizons | 74.5% | — |
| Vending-Bench 2 | 5,940 | — |

## Reasoning

- GPT-5.3 Codex: —
- o3-mini: 16.3 (#305)

| Benchmark | GPT-5.3 Codex | o3-mini |
|---|---|---|
| Epoch Capabilities Index | 156.77 | 140.34 |
| ARC-AGI-2 | — | 3% |
| SimpleBench | — | 22.8% |
| ARC-AGI-1 | — | 34.5% |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 17% |
| LiveBench Reasoning | — | 89.6% |
| LMArena Hard Prompts | — | 1366 |
| Mystery Game Puzzles | — | 7% |
| DTBench | — | 68.8% |
| LiveBench Data Analysis | — | 70.6% |
| LMCA | — | 19% |
| ForecastBench | — | 59.6 |
| LiveBench | — | 75.9% |

## Math

- GPT-5.3 Codex: —
- o3-mini: 28.1 (#244)

| Benchmark | GPT-5.3 Codex | o3-mini |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 18.6% |
| FrontierMath Tier 4 | — | 0% |
| OTIS Mock AIME 2024-2025 | — | 76.9% |
| LiveBench Math | — | 77.3% |
| LMArena Math | — | 1396 |
| MATH Level 5 | — | 96.5% |
| FrontierMath (Feb 2025 set) | — | 12.4% |
| FrontierMath Tier 4 (v1) | — | 4.2% |

## Knowledge

- GPT-5.3 Codex: —
- o3-mini: 38.3 (#146)

| Benchmark | GPT-5.3 Codex | o3-mini |
|---|---|---|
| GPQA Diamond | — | 77% |
| SimpleQA Verified | — | 15.3% |
| Confabulations | — | 17.9% |
| LMArena Expert | — | 1364 |

## Multilingual

- GPT-5.3 Codex: —
- o3-mini: 45.7 (#164)

| Benchmark | GPT-5.3 Codex | o3-mini |
|---|---|---|
| LMArena Non-English | — | 1319 |
| LMArena Chinese | — | 1379 |
| LMArena French | — | 1334 |
| LMArena German | — | 1303 |
| LMArena Japanese | — | 1286 |
| LMArena Korean | — | 1314 |
| LMArena Russian | — | 1304 |
| LMArena Spanish | — | 1321 |

## Instruction Following

- GPT-5.3 Codex: —
- o3-mini: 75.1 (#72)

| Benchmark | GPT-5.3 Codex | o3-mini |
|---|---|---|
| LiveBench Instruction Following | — | 84.4% |
| LMArena Instruction Following | — | 1337 |

## Long Context

- GPT-5.3 Codex: —
- o3-mini: 33.8 (#256)

| Benchmark | GPT-5.3 Codex | o3-mini |
|---|---|---|
| Fiction.LiveBench | — | 50% |
| LMArena Longer Query | — | 1343 |

## Writing & Preference

- GPT-5.3 Codex: —
- o3-mini: 50.3 (#182)

| Benchmark | GPT-5.3 Codex | o3-mini |
|---|---|---|
| LMArena Text | — | 1337 |
| LMArena Creative Writing | — | 1286 |
| Short-Story Creative Writing | — | 61.7% |
| LMArena Multi-Turn | — | 1320 |
| LiveBench Language | — | 50.7% |

## FAQ

### Is GPT-5.3 Codex better than o3-mini?

GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 36.7 on the Noometry Index. o3-mini costs 2.5× less per token, which makes it the better buy when GPT-5.3 Codex's lead doesn't matter for your workload.

### Which is cheaper, GPT-5.3 Codex or o3-mini?

o3-mini is cheaper. It lists at $1.10 per million input tokens and $4.40 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.

### Is GPT-5.3 Codex or o3-mini better for coding?

GPT-5.3 Codex scores higher on coding benchmarks: 48.6 versus 40.8 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.3 Codex does, with 400K tokens against 200K.

### How many benchmarks do GPT-5.3 Codex and o3-mini share?

2 benchmarks have published results for both models. GPT-5.3 Codex has 8 scored results on Noometry and o3-mini has 51.