# Gemma 3 4B vs GPT-5 Nano

> GPT-5 Nano is the stronger model overall, scoring 33.4 to 27.9 on the Noometry Index. Gemma 3 4B costs 2.8× less per token, which makes it the better buy when GPT-5 Nano's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemma-3-4b-vs-gpt-5-nano
- Last updated: 2026-10-10
- Shared benchmarks: 22

## Summary

- They share 22 benchmarks with published results for both. Gemma 3 4B scores higher in 3 categories and GPT-5 Nano in 6 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-5 Nano leads 35.8 to 11.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 7.5% for Gemma 3 4B and 81.1% for GPT-5 Nano.
- Gemma 3 4B is cheaper at $0.04 / $0.08 per million input/output tokens, against $0.05 / $0.40 for GPT-5 Nano.
- GPT-5 Nano 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 Nano |
|---|---|---|
| Provider | Google | OpenAI |
| Noometry Index | 27.9 | 33.4 |
| Rank | 320 | 234 |
| Context | 131K | 400K |
| Input $/M | $0.04 | $0.05 |
| Output $/M | $0.08 | $0.40 |
| Weights | Open | Proprietary |

## Coding

- Gemma 3 4B: 35.3 (#214)
- GPT-5 Nano: 33.3 (#248)

| Benchmark | Gemma 3 4B | GPT-5 Nano |
|---|---|---|
| LMArena Coding | 1230 | 1351 |
| SWE-bench Verified (bash only) | — | 34.8% |
| WeirdML | — | 38.1% |
| ALE-Bench | — | 718.67 |

## Agentic & Tool Use

- Gemma 3 4B: 20.7 (#134)
- GPT-5 Nano: 25.6 (#99)

| Benchmark | Gemma 3 4B | GPT-5 Nano |
|---|---|---|
| Berkeley Function Calling Leaderboard | 19.6% | 51.5% |
| Terminal-Bench | — | 21.8% |

## Reasoning

- Gemma 3 4B: 12.7 (#330)
- GPT-5 Nano: 16.4 (#291)

| Benchmark | Gemma 3 4B | GPT-5 Nano |
|---|---|---|
| Kagi LLM Benchmark | 25.2% | 62.2% |
| Chess Puzzles | 0% | 27% |
| LMArena Hard Prompts | 1253 | 1329 |
| DTBench | 50.9% | 62.7% |
| LMCA | 2.8% | 7.9% |
| Epoch Capabilities Index | 116.02 | 139.39 |
| ARC-AGI-2 | — | 2.6% |
| ARC-AGI-1 | — | 20.7% |
| Mystery Game Puzzles | — | 9% |
| ForecastBench | — | 59.1 |

## Math

- Gemma 3 4B: 15.8 (#286)
- GPT-5 Nano: 29.1 (#221)

| Benchmark | Gemma 3 4B | GPT-5 Nano |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 7.5% | 81.1% |
| LMArena Math | 1239 | 1318 |
| FrontierMath (Tiers 1-3) | — | 20% |
| FrontierMath Tier 4 | — | 2.4% |
| ProofBench | — | 12% |
| Omni-MATH | — | 54.6% |
| MATH Level 5 | — | 95.2% |
| FrontierMath (Feb 2025 set) | — | 8.3% |
| FrontierMath Tier 4 (v1) | — | 2.1% |

## Knowledge

- Gemma 3 4B: 11.8 (#294)
- GPT-5 Nano: 35.8 (#166)

| Benchmark | Gemma 3 4B | GPT-5 Nano |
|---|---|---|
| GPQA Diamond | 23.2% | 69.4% |
| Vectara Hallucination Rate | 6.4% | 10.5% |
| LMArena Expert | 1223 | 1321 |
| SimpleQA Verified | — | 11.7% |
| MMLU-Pro | — | 77.8% |
| GPQA (HELM) | — | 67.9% |

## Multimodal

- Gemma 3 4B: —
- GPT-5 Nano: 30.7 (#102)

| Benchmark | Gemma 3 4B | GPT-5 Nano |
|---|---|---|
| LMArena Vision | — | 1159 |
| VPCT | — | 37.2% |

## Multilingual

- Gemma 3 4B: 42.7 (#189)
- GPT-5 Nano: 45.5 (#167)

| Benchmark | Gemma 3 4B | GPT-5 Nano |
|---|---|---|
| LMArena Non-English | 1273 | 1313 |
| LMArena German | 1281 | 1329 |
| LMArena Russian | 1294 | 1296 |
| LMArena Chinese | — | 1355 |
| LMArena Korean | — | 1269 |
| LMArena Spanish | — | 1360 |

## Instruction Following

- Gemma 3 4B: 65.4 (#219)
- GPT-5 Nano: 75.2 (#72)

| Benchmark | Gemma 3 4B | GPT-5 Nano |
|---|---|---|
| LMArena Instruction Following | 1239 | 1306 |
| IFEval | — | 93.2% |

## Long Context

- Gemma 3 4B: 38.6 (#189)
- GPT-5 Nano: 31.3 (#275)

| Benchmark | Gemma 3 4B | GPT-5 Nano |
|---|---|---|
| LMArena Longer Query | 1274 | 1313 |
| Fiction.LiveBench | — | 44.4% |

## Writing & Preference

- Gemma 3 4B: 42.2 (#234)
- GPT-5 Nano: 39.4 (#244)

| Benchmark | Gemma 3 4B | GPT-5 Nano |
|---|---|---|
| LMArena Text | 1291 | 1320 |
| LMArena Creative Writing | 1270 | 1250 |
| EQ-Bench Creative Writing | 1068 | 705 |
| LMArena Multi-Turn | 1255 | 1311 |
| WildBench | — | 80.6% |

## FAQ

### Is Gemma 3 4B better than GPT-5 Nano?

GPT-5 Nano is the stronger model overall, scoring 33.4 to 27.9 on the Noometry Index. Gemma 3 4B costs 2.8× less per token, which makes it the better buy when GPT-5 Nano's lead doesn't matter for your workload.

### Which is cheaper, Gemma 3 4B or GPT-5 Nano?

Gemma 3 4B is cheaper. It lists at $0.04 per million input tokens and $0.08 per million output tokens; GPT-5 Nano lists at $0.05 and $0.40.

### Is Gemma 3 4B or GPT-5 Nano better for coding?

Gemma 3 4B scores higher on coding benchmarks: 35.3 versus 33.3 in the Noometry coding category.

### Which has the bigger context window?

GPT-5 Nano does, with 400K tokens against 131K.

### How many benchmarks do Gemma 3 4B and GPT-5 Nano share?

22 benchmarks have published results for both models. Gemma 3 4B has 22 scored results on Noometry and GPT-5 Nano has 48.