# Gemma 3n E4b IT vs GPT-5.3 Codex

> GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 37.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gemma-3n-e4b-it-vs-gpt-5-3-codex
- Last updated: 2026-10-11
- Shared benchmarks: 0

## Summary

- The widest gap is in coding, where GPT-5.3 Codex leads 48.6 to 37.0.
- Gemma 3n E4b IT has downloadable open weights; the other is API-only.

## Snapshot

| | Gemma 3n E4b IT | GPT-5.3 Codex |
|---|---|---|
| Provider | Google | OpenAI |
| Noometry Index | 37.3 | 45.8 |
| Rank | 206 | 69 |
| Context | — | 400K |
| Input $/M | — | $1.75 |
| Output $/M | — | $14 |
| Weights | Open | Proprietary |

## Coding

- Gemma 3n E4b IT: 37.0 (#198)
- GPT-5.3 Codex: 48.6 (#56)

| Benchmark | Gemma 3n E4b IT | GPT-5.3 Codex |
|---|---|---|
| SWE-bench Verified | — | 74.8% |
| LMArena WebDev | — | 1409 |
| WeirdML | — | 79.3% |
| LMArena Coding | 1268 | — |
| ALE-Bench | — | 1,655 |

## Agentic & Tool Use

- Gemma 3n E4b IT: —
- GPT-5.3 Codex: 48.0 (#9)

| Benchmark | Gemma 3n E4b IT | GPT-5.3 Codex |
|---|---|---|
| Terminal-Bench | — | 78.4% |
| METR Time Horizons | — | 74.5% |
| Vending-Bench 2 | — | 5,940 |

## Reasoning

- Gemma 3n E4b IT: 19.9 (#247)
- GPT-5.3 Codex: —

| Benchmark | Gemma 3n E4b IT | GPT-5.3 Codex |
|---|---|---|
| Kagi LLM Benchmark | 31.5% | — |
| LMArena Hard Prompts | 1284 | — |
| Epoch Capabilities Index | — | 156.77 |

## Math

- Gemma 3n E4b IT: 35.1 (#188)
- GPT-5.3 Codex: —

| Benchmark | Gemma 3n E4b IT | GPT-5.3 Codex |
|---|---|---|
| LMArena Math | 1251 | — |

## Knowledge

- Gemma 3n E4b IT: 34.2 (#198)
- GPT-5.3 Codex: —

| Benchmark | Gemma 3n E4b IT | GPT-5.3 Codex |
|---|---|---|
| LMArena Expert | 1246 | — |

## Multilingual

- Gemma 3n E4b IT: 43.4 (#183)
- GPT-5.3 Codex: —

| Benchmark | Gemma 3n E4b IT | GPT-5.3 Codex |
|---|---|---|
| LMArena Non-English | 1285 | — |
| LMArena Chinese | 1309 | — |
| LMArena French | 1330 | — |
| LMArena German | 1311 | — |
| LMArena Japanese | 1272 | — |
| LMArena Korean | 1259 | — |
| LMArena Russian | 1288 | — |
| LMArena Spanish | 1305 | — |

## Instruction Following

- Gemma 3n E4b IT: 66.1 (#210)
- GPT-5.3 Codex: —

| Benchmark | Gemma 3n E4b IT | GPT-5.3 Codex |
|---|---|---|
| LMArena Instruction Following | 1255 | — |

## Long Context

- Gemma 3n E4b IT: 38.7 (#191)
- GPT-5.3 Codex: —

| Benchmark | Gemma 3n E4b IT | GPT-5.3 Codex |
|---|---|---|
| LMArena Longer Query | 1276 | — |

## Writing & Preference

- Gemma 3n E4b IT: 50.1 (#186)
- GPT-5.3 Codex: —

| Benchmark | Gemma 3n E4b IT | GPT-5.3 Codex |
|---|---|---|
| LMArena Text | 1306 | — |
| LMArena Creative Writing | 1287 | — |
| LMArena Multi-Turn | 1276 | — |

## FAQ

### Is Gemma 3n E4b IT better than GPT-5.3 Codex?

GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 37.3 on the Noometry Index.

### Is Gemma 3n E4b IT or GPT-5.3 Codex better for coding?

GPT-5.3 Codex scores higher on coding benchmarks: 48.6 versus 37.0 in the Noometry coding category.

### How many benchmarks do Gemma 3n E4b IT and GPT-5.3 Codex share?

0 benchmarks have published results for both models. Gemma 3n E4b IT has 18 scored results on Noometry and GPT-5.3 Codex has 8.