# GPT-4o mini vs GPT-5.3 Codex

> GPT-5.3 Codex is the stronger model overall, scoring 45.5 to 25.4 on the Noometry Index. GPT-4o mini costs 18× 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-4o-mini-vs-gpt-5-3-codex
- Last updated: 2026-10-10
- Shared benchmarks: 2

## Summary

- They share 2 benchmarks with published results for both. GPT-4o mini scores higher in 0 categories and GPT-5.3 Codex in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where GPT-5.3 Codex leads 48.5 to 21.6.
- The biggest single-benchmark swing is WeirdML: 11.8% for GPT-4o mini and 79.3% for GPT-5.3 Codex.
- GPT-4o mini is cheaper at $0.15 / $0.60 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- GPT-5.3 Codex accepts more context: 400K tokens versus 128K.

## Snapshot

| | GPT-4o mini | GPT-5.3 Codex |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 25.4 | 45.5 |
| Rank | 337 | 61 |
| Context | 128K | 400K |
| Input $/M | $0.15 | $1.75 |
| Output $/M | $0.60 | $14 |
| Weights | Proprietary | Proprietary |

## Coding

- GPT-4o mini: 21.6 (#330)
- GPT-5.3 Codex: 48.5 (#51)

| Benchmark | GPT-4o mini | GPT-5.3 Codex |
|---|---|---|
| WeirdML | 11.8% | 79.3% |
| SWE-bench Verified | — | 74.8% |
| Aider Polyglot | 3.6% | — |
| LMArena WebDev | — | 1408 |
| BigCodeBench Instruct | 46.1% | — |
| LiveBench Coding | 43.1% | — |
| LMArena Coding | 1290 | — |
| BigCodeBench Complete | 57.4% | — |
| ALE-Bench | — | 1,655 |
| HumanEval+ | 83.5% | — |
| MBPP+ | 72.2% | — |

## Agentic & Tool Use

- GPT-4o mini: 27.2 (#95)
- GPT-5.3 Codex: 47.8 (#9)

| Benchmark | GPT-4o mini | GPT-5.3 Codex |
|---|---|---|
| Terminal-Bench | — | 78.4% |
| BALROG | 17.4% | — |
| METR Time Horizons | — | 74.5% |
| Vending-Bench 2 | — | 5,940 |

## Reasoning

- GPT-4o mini: 8.7 (#343)
- GPT-5.3 Codex: —

| Benchmark | GPT-4o mini | GPT-5.3 Codex |
|---|---|---|
| Epoch Capabilities Index | 126.56 | 156.84 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 10.7% | — |
| Kagi LLM Benchmark | 28.8% | — |
| Chess Puzzles | 0% | — |
| LiveBench Reasoning | 32.8% | — |
| LMArena Hard Prompts | 1267 | — |
| Mystery Game Puzzles | 12% | — |
| DTBench | 54.4% | — |
| LiveBench Data Analysis | 50% | — |
| LMCA | 10.4% | — |
| LiveBench | 41.3% | — |
| PIQA | 88.7% | — |

## Math

- GPT-4o mini: 9.9 (#307)
- GPT-5.3 Codex: —

| Benchmark | GPT-4o mini | GPT-5.3 Codex |
|---|---|---|
| FrontierMath (Tiers 1-3) | 0.7% | — |
| OTIS Mock AIME 2024-2025 | 6.9% | — |
| Omni-MATH | 28% | — |
| LiveBench Math | 36.3% | — |
| LMArena Math | 1267 | — |
| MATH Level 5 | 52.6% | — |
| GSM8K | 91.3% | — |

## Knowledge

- GPT-4o mini: 17.7 (#279)
- GPT-5.3 Codex: —

| Benchmark | GPT-4o mini | GPT-5.3 Codex |
|---|---|---|
| GPQA Diamond | 37.7% | — |
| SimpleQA Verified | 8.3% | — |
| MMLU-Pro | 60.3% | — |
| Confabulations | 37.2% | — |
| GPQA (HELM) | 36.8% | — |
| LMArena Expert | 1235 | — |
| BoolQ | 88.7% | — |
| MMLU | 81.8% | — |

## Multimodal

- GPT-4o mini: 25.3 (#117)
- GPT-5.3 Codex: —

| Benchmark | GPT-4o mini | GPT-5.3 Codex |
|---|---|---|
| LMArena Vision | 1066 | — |
| Video-MME | 64.8% | — |
| GeoBench | 64% | — |
| VPCT | 34% | — |

## Multilingual

- GPT-4o mini: 42.2 (#194)
- GPT-5.3 Codex: —

| Benchmark | GPT-4o mini | GPT-5.3 Codex |
|---|---|---|
| LMArena Non-English | 1266 | — |
| LMArena Chinese | 1264 | — |
| LMArena French | 1296 | — |
| LMArena German | 1272 | — |
| LMArena Japanese | 1216 | — |
| LMArena Korean | 1195 | — |
| LMArena Russian | 1275 | — |
| LMArena Spanish | 1276 | — |

## Instruction Following

- GPT-4o mini: 62.1 (#234)
- GPT-5.3 Codex: —

| Benchmark | GPT-4o mini | GPT-5.3 Codex |
|---|---|---|
| LiveBench Instruction Following | 56.8% | — |
| IFEval | 78.2% | — |
| LMArena Instruction Following | 1259 | — |

## Long Context

- GPT-4o mini: 39.1 (#181)
- GPT-5.3 Codex: —

| Benchmark | GPT-4o mini | GPT-5.3 Codex |
|---|---|---|
| LMArena Longer Query | 1289 | — |

## Writing & Preference

- GPT-4o mini: 39.7 (#243)
- GPT-5.3 Codex: —

| Benchmark | GPT-4o mini | GPT-5.3 Codex |
|---|---|---|
| LMArena Text | 1286 | — |
| LMArena Creative Writing | 1268 | — |
| Short-Story Creative Writing | 67.2% | — |
| EQ-Bench Creative Writing | 873 | — |
| WildBench | 79.1% | — |
| LMArena Multi-Turn | 1285 | — |
| LiveBench Language | 28.6% | — |

## FAQ

### Is GPT-4o mini better than GPT-5.3 Codex?

GPT-5.3 Codex is the stronger model overall, scoring 45.5 to 25.4 on the Noometry Index. GPT-4o mini costs 18× 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-4o mini or GPT-5.3 Codex?

GPT-4o mini is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.

### Is GPT-4o mini or GPT-5.3 Codex better for coding?

GPT-5.3 Codex scores higher on coding benchmarks: 48.5 versus 21.6 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.3 Codex does, with 400K tokens against 128K.

### How many benchmarks do GPT-4o mini and GPT-5.3 Codex share?

2 benchmarks have published results for both models. GPT-4o mini has 60 scored results on Noometry and GPT-5.3 Codex has 8.