# Gemma 3 4B vs GPT-5.3 Codex

> GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 28.1 on the Noometry Index. Gemma 3 4B costs 96× 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/gemma-3-4b-vs-gpt-5-3-codex
- Last updated: 2026-10-11
- Shared benchmarks: 1

## Summary

- They share 1 benchmark with published results for both. Gemma 3 4B 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 agentic & tool use, where GPT-5.3 Codex leads 48.0 to 20.9.
- Gemma 3 4B is cheaper at $0.04 / $0.08 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- GPT-5.3 Codex accepts more context: 400K tokens versus 131K.
- Gemma 3 4B has downloadable open weights; the other is API-only.

## Snapshot

| | Gemma 3 4B | GPT-5.3 Codex |
|---|---|---|
| Provider | Google | OpenAI |
| Noometry Index | 28.1 | 45.8 |
| Rank | 326 | 69 |
| Context | 131K | 400K |
| Input $/M | $0.04 | $1.75 |
| Output $/M | $0.08 | $14 |
| Weights | Open | Proprietary |

## Coding

- Gemma 3 4B: 35.9 (#215)
- GPT-5.3 Codex: 48.6 (#56)

| Benchmark | Gemma 3 4B | GPT-5.3 Codex |
|---|---|---|
| SWE-bench Verified | — | 74.8% |
| LMArena WebDev | — | 1409 |
| WeirdML | — | 79.3% |
| LMArena Coding | 1230 | — |
| ALE-Bench | — | 1,655 |

## Agentic & Tool Use

- Gemma 3 4B: 20.9 (#142)
- GPT-5.3 Codex: 48.0 (#9)

| Benchmark | Gemma 3 4B | GPT-5.3 Codex |
|---|---|---|
| Terminal-Bench | — | 78.4% |
| Berkeley Function Calling Leaderboard | 19.6% | — |
| METR Time Horizons | — | 74.5% |
| Vending-Bench 2 | — | 5,940 |

## Reasoning

- Gemma 3 4B: 13.2 (#335)
- GPT-5.3 Codex: —

| Benchmark | Gemma 3 4B | GPT-5.3 Codex |
|---|---|---|
| Epoch Capabilities Index | 116.02 | 156.77 |
| Kagi LLM Benchmark | 25.2% | — |
| Chess Puzzles | 0% | — |
| LMArena Hard Prompts | 1253 | — |
| DTBench | 50.9% | — |
| LMCA | 2.8% | — |

## Math

- Gemma 3 4B: 16.8 (#292)
- GPT-5.3 Codex: —

| Benchmark | Gemma 3 4B | GPT-5.3 Codex |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 7.5% | — |
| LMArena Math | 1239 | — |

## Knowledge

- Gemma 3 4B: 11.8 (#299)
- GPT-5.3 Codex: —

| Benchmark | Gemma 3 4B | GPT-5.3 Codex |
|---|---|---|
| GPQA Diamond | 23.2% | — |
| Vectara Hallucination Rate | 6.4% | — |
| LMArena Expert | 1223 | — |

## Multilingual

- Gemma 3 4B: 42.5 (#194)
- GPT-5.3 Codex: —

| Benchmark | Gemma 3 4B | GPT-5.3 Codex |
|---|---|---|
| LMArena Non-English | 1273 | — |
| LMArena German | 1281 | — |
| LMArena Russian | 1294 | — |

## Instruction Following

- Gemma 3 4B: 65.2 (#225)
- GPT-5.3 Codex: —

| Benchmark | Gemma 3 4B | GPT-5.3 Codex |
|---|---|---|
| LMArena Instruction Following | 1239 | — |

## Long Context

- Gemma 3 4B: 38.7 (#194)
- GPT-5.3 Codex: —

| Benchmark | Gemma 3 4B | GPT-5.3 Codex |
|---|---|---|
| LMArena Longer Query | 1273 | — |

## Writing & Preference

- Gemma 3 4B: 42.0 (#239)
- GPT-5.3 Codex: —

| Benchmark | Gemma 3 4B | GPT-5.3 Codex |
|---|---|---|
| LMArena Text | 1291 | — |
| LMArena Creative Writing | 1271 | — |
| EQ-Bench Creative Writing | 1068 | — |
| LMArena Multi-Turn | 1255 | — |

## FAQ

### Is Gemma 3 4B better than GPT-5.3 Codex?

GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 28.1 on the Noometry Index. Gemma 3 4B costs 96× 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, Gemma 3 4B or GPT-5.3 Codex?

Gemma 3 4B is cheaper. It lists at $0.04 per million input tokens and $0.08 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.

### Is Gemma 3 4B or GPT-5.3 Codex better for coding?

GPT-5.3 Codex scores higher on coding benchmarks: 48.6 versus 35.9 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.3 Codex does, with 400K tokens against 131K.

### How many benchmarks do Gemma 3 4B and GPT-5.3 Codex share?

1 benchmark has published results for both models. Gemma 3 4B has 22 scored results on Noometry and GPT-5.3 Codex has 8.