# Gemma 3n E4b IT vs Llama 3.1-8B

> Gemma 3n E4b IT is the stronger model overall, scoring 36.7 to 22.8 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gemma-3n-e4b-it-vs-llama-3-1-8b
- Last updated: 2026-10-10
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. Gemma 3n E4b IT scores higher in 8 categories and Llama 3.1-8B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Gemma 3n E4b IT leads 33.6 to 8.0.
- Llama 3.1-8B is cheaper at $0.05 / $0.08 per million input/output tokens, against $0.06 / $0.12 for Gemma 3n E4b IT.
- Llama 3.1-8B accepts more context: 128K tokens versus 33K.

## Snapshot

| | Gemma 3n E4b IT | Llama 3.1-8B |
|---|---|---|
| Provider | Google | Meta |
| Noometry Index | 36.7 | 22.8 |
| Rank | 203 | 347 |
| Context | 33K | 128K |
| Input $/M | $0.06 | $0.05 |
| Output $/M | $0.12 | $0.08 |
| Weights | Open | Open |

## Coding

- Gemma 3n E4b IT: 36.4 (#193)
- Llama 3.1-8B: 19.9 (#335)

| Benchmark | Gemma 3n E4b IT | Llama 3.1-8B |
|---|---|---|
| LMArena Coding | 1269 | 1195 |
| SciCode | — | 13.2% |
| WeirdML | — | 1.7% |
| BigCodeBench Instruct | — | 32.8% |
| BigCodeBench Complete | — | 40.5% |
| HumanEval+ | — | 62.8% |
| MBPP+ | — | 55.6% |

## Agentic & Tool Use

- Gemma 3n E4b IT: —
- Llama 3.1-8B: 22.3 (#123)

| Benchmark | Gemma 3n E4b IT | Llama 3.1-8B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 25.8% |
| BALROG | — | 15.1% |

## Reasoning

- Gemma 3n E4b IT: 19.2 (#239)
- Llama 3.1-8B: 14.5 (#316)

| Benchmark | Gemma 3n E4b IT | Llama 3.1-8B |
|---|---|---|
| LMArena Hard Prompts | 1284 | 1175 |
| Kagi LLM Benchmark | 31.5% | — |
| CritPt | — | 0% |
| Chess Puzzles | — | 0% |
| DTBench | — | 50.9% |
| LMCA | — | 5.4% |
| Epoch Capabilities Index | — | 116.48 |
| PIQA | — | 81.2% |

## Math

- Gemma 3n E4b IT: 32.5 (#186)
- Llama 3.1-8B: 9.5 (#311)

| Benchmark | Gemma 3n E4b IT | Llama 3.1-8B |
|---|---|---|
| LMArena Math | 1251 | 1179 |
| OTIS Mock AIME 2024-2025 | — | 1.7% |
| Omni-MATH | — | 13.7% |
| MATH Level 5 | — | 22.9% |
| GSM8K | — | 82.4% |

## Knowledge

- Gemma 3n E4b IT: 33.6 (#193)
- Llama 3.1-8B: 8.0 (#302)

| Benchmark | Gemma 3n E4b IT | Llama 3.1-8B |
|---|---|---|
| LMArena Expert | 1245 | 1144 |
| GPQA Diamond | — | 27% |
| MMLU-Pro | — | 40.6% |
| GPQA (HELM) | — | 24.7% |
| BoolQ | — | 82.8% |
| MMLU | — | 56.1% |

## Multilingual

- Gemma 3n E4b IT: 43.5 (#179)
- Llama 3.1-8B: 34.2 (#244)

| Benchmark | Gemma 3n E4b IT | Llama 3.1-8B |
|---|---|---|
| LMArena Non-English | 1285 | 1148 |
| LMArena Chinese | 1310 | 1151 |
| LMArena French | 1330 | 1176 |
| LMArena German | 1312 | 1144 |
| LMArena Japanese | 1274 | 1061 |
| LMArena Korean | 1259 | 1053 |
| LMArena Russian | 1288 | 1158 |
| LMArena Spanish | 1305 | 1169 |

## Instruction Following

- Gemma 3n E4b IT: 66.3 (#205)
- Llama 3.1-8B: 59.1 (#253)

| Benchmark | Gemma 3n E4b IT | Llama 3.1-8B |
|---|---|---|
| LMArena Instruction Following | 1255 | 1159 |
| IFEval | — | 74.3% |

## Long Context

- Gemma 3n E4b IT: 38.8 (#185)
- Llama 3.1-8B: 35.8 (#233)

| Benchmark | Gemma 3n E4b IT | Llama 3.1-8B |
|---|---|---|
| LMArena Longer Query | 1277 | 1182 |

## Writing & Preference

- Gemma 3n E4b IT: 50.3 (#181)
- Llama 3.1-8B: 29.9 (#285)

| Benchmark | Gemma 3n E4b IT | Llama 3.1-8B |
|---|---|---|
| LMArena Text | 1306 | 1187 |
| LMArena Creative Writing | 1287 | 1154 |
| LMArena Multi-Turn | 1276 | 1172 |
| EQ-Bench Creative Writing | — | 713 |
| WildBench | — | 68.7% |

## FAQ

### Is Gemma 3n E4b IT better than Llama 3.1-8B?

Gemma 3n E4b IT is the stronger model overall, scoring 36.7 to 22.8 on the Noometry Index.

### Which is cheaper, Gemma 3n E4b IT or Llama 3.1-8B?

Llama 3.1-8B is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; Gemma 3n E4b IT lists at $0.06 and $0.12.

### Is Gemma 3n E4b IT or Llama 3.1-8B better for coding?

Gemma 3n E4b IT scores higher on coding benchmarks: 36.4 versus 19.9 in the Noometry coding category.

### Which has the bigger context window?

Llama 3.1-8B does, with 128K tokens against 33K.

### How many benchmarks do Gemma 3n E4b IT and Llama 3.1-8B share?

17 benchmarks have published results for both models. Gemma 3n E4b IT has 18 scored results on Noometry and Llama 3.1-8B has 43.