# Gemma 3n E4b IT vs Llama 4 Maverick

> Gemma 3n E4b IT is the stronger model overall, scoring 36.7 to 30.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gemma-3n-e4b-it-vs-llama-4-maverick
- Last updated: 2026-10-10
- Shared benchmarks: 18

## Summary

- They share 18 benchmarks with published results for both. Gemma 3n E4b IT scores higher in 7 categories and Llama 4 Maverick in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Gemma 3n E4b IT leads 50.3 to 39.0.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 31.5% for Gemma 3n E4b IT and 55.9% for Llama 4 Maverick.
- Gemma 3n E4b IT is cheaper at $0.06 / $0.12 per million input/output tokens, against $0.19 / $0.65 for Llama 4 Maverick.
- Llama 4 Maverick accepts more context: 128K tokens versus 33K.

## Snapshot

| | Gemma 3n E4b IT | Llama 4 Maverick |
|---|---|---|
| Provider | Google | Meta |
| Noometry Index | 36.7 | 30.6 |
| Rank | 203 | 276 |
| Context | 33K | 128K |
| Input $/M | $0.06 | $0.19 |
| Output $/M | $0.12 | $0.65 |
| Weights | Open | Open |

## Coding

- Gemma 3n E4b IT: 36.4 (#193)
- Llama 4 Maverick: 26.3 (#318)

| Benchmark | Gemma 3n E4b IT | Llama 4 Maverick |
|---|---|---|
| LMArena Coding | 1269 | 1302 |
| SWE-bench Verified (bash only) | — | 21% |
| Aider Polyglot | — | 15.6% |
| SciCode | — | 33.1% |
| WeirdML | — | 24.5% |
| BigCodeBench Instruct | — | 49.7% |
| BigCodeBench Complete | — | 61.4% |
| ALE-Bench | — | 172.97 |

## Agentic & Tool Use

- Gemma 3n E4b IT: —
- Llama 4 Maverick: 27.9 (#86)

| Benchmark | Gemma 3n E4b IT | Llama 4 Maverick |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 37.3% |

## Reasoning

- Gemma 3n E4b IT: 19.2 (#239)
- Llama 4 Maverick: 10.1 (#337)

| Benchmark | Gemma 3n E4b IT | Llama 4 Maverick |
|---|---|---|
| Kagi LLM Benchmark | 31.5% | 55.9% |
| LMArena Hard Prompts | 1284 | 1281 |
| ARC-AGI-2 | — | 0% |
| SimpleBench | — | 27.7% |
| NYT Connections (extended) | — | 8% |
| ARC-AGI-1 | — | 4.4% |
| CritPt | — | 0% |
| EnigmaEval | — | 0.6% |
| DTBench | — | 61.9% |
| LMCA | — | 15.9% |
| Epoch Capabilities Index | — | 132.2 |
| ForecastBench | — | 57.5 |

## Math

- Gemma 3n E4b IT: 32.5 (#186)
- Llama 4 Maverick: 24.6 (#256)

| Benchmark | Gemma 3n E4b IT | Llama 4 Maverick |
|---|---|---|
| LMArena Math | 1251 | 1299 |
| OTIS Mock AIME 2024-2025 | — | 20.6% |
| Omni-MATH | — | 42.2% |
| MATH Level 5 | — | 73% |
| FrontierMath (Feb 2025 set) | — | 0.7% |

## Knowledge

- Gemma 3n E4b IT: 33.6 (#193)
- Llama 4 Maverick: 33.3 (#196)

| Benchmark | Gemma 3n E4b IT | Llama 4 Maverick |
|---|---|---|
| LMArena Expert | 1245 | 1259 |
| GPQA Diamond | — | 67% |
| Humanity's Last Exam | — | 5.7% |
| MMLU-Pro | — | 81% |
| Confabulations | — | 22.6% |
| Vectara Hallucination Rate | — | 8.2% |
| GPQA (HELM) | — | 65% |

## Multimodal

- Gemma 3n E4b IT: —
- Llama 4 Maverick: 30.9 (#100)

| Benchmark | Gemma 3n E4b IT | Llama 4 Maverick |
|---|---|---|
| LMArena Vision | — | 1141 |
| GeoBench | — | 52% |
| SpatialViz-Bench | — | 31.8% |

## Multilingual

- Gemma 3n E4b IT: 43.5 (#179)
- Llama 4 Maverick: 42.4 (#190)

| Benchmark | Gemma 3n E4b IT | Llama 4 Maverick |
|---|---|---|
| LMArena Non-English | 1285 | 1269 |
| LMArena Chinese | 1310 | 1277 |
| LMArena French | 1330 | 1258 |
| LMArena German | 1312 | 1291 |
| LMArena Japanese | 1274 | 1207 |
| LMArena Korean | 1259 | 1203 |
| LMArena Russian | 1288 | 1286 |
| LMArena Spanish | 1305 | 1293 |

## Instruction Following

- Gemma 3n E4b IT: 66.3 (#205)
- Llama 4 Maverick: 71.9 (#140)

| Benchmark | Gemma 3n E4b IT | Llama 4 Maverick |
|---|---|---|
| LMArena Instruction Following | 1255 | 1267 |
| IFEval | — | 90.8% |

## Long Context

- Gemma 3n E4b IT: 38.8 (#185)
- Llama 4 Maverick: 31.4 (#274)

| Benchmark | Gemma 3n E4b IT | Llama 4 Maverick |
|---|---|---|
| LMArena Longer Query | 1277 | 1280 |
| Fiction.LiveBench | — | 46.2% |

## Writing & Preference

- Gemma 3n E4b IT: 50.3 (#181)
- Llama 4 Maverick: 39.0 (#247)

| Benchmark | Gemma 3n E4b IT | Llama 4 Maverick |
|---|---|---|
| LMArena Text | 1306 | 1287 |
| LMArena Creative Writing | 1287 | 1266 |
| LMArena Multi-Turn | 1276 | 1289 |
| Short-Story Creative Writing | — | 62% |
| EQ-Bench Creative Writing | — | 860 |
| WildBench | — | 80% |

## FAQ

### Is Gemma 3n E4b IT better than Llama 4 Maverick?

Gemma 3n E4b IT is the stronger model overall, scoring 36.7 to 30.6 on the Noometry Index.

### Which is cheaper, Gemma 3n E4b IT or Llama 4 Maverick?

Gemma 3n E4b IT is cheaper. It lists at $0.06 per million input tokens and $0.12 per million output tokens; Llama 4 Maverick lists at $0.19 and $0.65.

### Is Gemma 3n E4b IT or Llama 4 Maverick better for coding?

Gemma 3n E4b IT scores higher on coding benchmarks: 36.4 versus 26.3 in the Noometry coding category.

### Which has the bigger context window?

Llama 4 Maverick does, with 128K tokens against 33K.

### How many benchmarks do Gemma 3n E4b IT and Llama 4 Maverick share?

18 benchmarks have published results for both models. Gemma 3n E4b IT has 18 scored results on Noometry and Llama 4 Maverick has 54.