# Gemma 2 27B vs Llama-3.3-70B-Instruct

> Llama-3.3-70B-Instruct is the stronger model overall, scoring 30.3 to 29.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gemma-2-27b-vs-llama-3-3-70b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 34

## Summary

- They share 34 benchmarks with published results for both. Gemma 2 27B scores higher in 3 categories and Llama-3.3-70B-Instruct in 5 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Llama-3.3-70B-Instruct leads 30.5 to 18.9.
- The biggest single-benchmark swing is LiveBench Instruction Following: 58.1% for Gemma 2 27B and 82.7% for Llama-3.3-70B-Instruct.
- Llama-3.3-70B-Instruct is cheaper at $0.10 / $0.32 per million input/output tokens, against $0.65 / $0.65 for Gemma 2 27B.
- Llama-3.3-70B-Instruct accepts more context: 128K tokens versus 8K.

## Snapshot

| | Gemma 2 27B | Llama-3.3-70B-Instruct |
|---|---|---|
| Provider | Google | Meta |
| Noometry Index | 29.2 | 30.3 |
| Rank | 302 | 283 |
| Context | 8K | 128K |
| Input $/M | $0.65 | $0.10 |
| Output $/M | $0.65 | $0.32 |
| Weights | Open | Open |

## Coding

- Gemma 2 27B: 33.5 (#243)
- Llama-3.3-70B-Instruct: 30.6 (#284)

| Benchmark | Gemma 2 27B | Llama-3.3-70B-Instruct |
|---|---|---|
| BigCodeBench Instruct | 42.8% | 46.9% |
| LiveBench Coding | 36% | 36.6% |
| LMArena Coding | 1211 | 1268 |
| BigCodeBench Complete | 52.5% | 57.5% |
| SciCode | — | 26% |
| WeirdML | — | 14.4% |

## Agentic & Tool Use

- Gemma 2 27B: —
- Llama-3.3-70B-Instruct: 25.6 (#100)

| Benchmark | Gemma 2 27B | Llama-3.3-70B-Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 31.9% |
| BALROG | — | 23% |

## Reasoning

- Gemma 2 27B: 14.8 (#313)
- Llama-3.3-70B-Instruct: 13.7 (#325)

| Benchmark | Gemma 2 27B | Llama-3.3-70B-Instruct |
|---|---|---|
| LiveBench Reasoning | 28.1% | 50.8% |
| LMArena Hard Prompts | 1199 | 1257 |
| DTBench | 48% | 59.5% |
| LiveBench Data Analysis | 47.9% | 49.5% |
| LMCA | 7.1% | 17.5% |
| Epoch Capabilities Index | 122.06 | 127.32 |
| LiveBench | 38.2% | 50.2% |
| SimpleBench | — | 19.9% |
| CritPt | — | 0% |
| ForecastBench | — | 58.6 |

## Math

- Gemma 2 27B: 10.0 (#306)
- Llama-3.3-70B-Instruct: 14.3 (#292)

| Benchmark | Gemma 2 27B | Llama-3.3-70B-Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.4% | 5.1% |
| LiveBench Math | 26.5% | 42.2% |
| LMArena Math | 1212 | 1268 |
| MATH Level 5 | 27.9% | 41.6% |

## Knowledge

- Gemma 2 27B: 18.9 (#275)
- Llama-3.3-70B-Instruct: 30.5 (#220)

| Benchmark | Gemma 2 27B | Llama-3.3-70B-Instruct |
|---|---|---|
| GPQA Diamond | 36.5% | 47.4% |
| Confabulations | 27.1% | 22.8% |
| LMArena Expert | 1172 | 1225 |
| MMLU | 75.7% | 86.3% |
| Vectara Hallucination Rate | — | 4.1% |

## Multilingual

- Gemma 2 27B: 38.8 (#221)
- Llama-3.3-70B-Instruct: 40.1 (#215)

| Benchmark | Gemma 2 27B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Non-English | 1217 | 1236 |
| LMArena Chinese | 1221 | 1217 |
| LMArena French | 1246 | 1280 |
| LMArena German | 1209 | 1251 |
| LMArena Japanese | 1175 | 1149 |
| LMArena Korean | 1174 | 1142 |
| LMArena Russian | 1234 | 1252 |
| LMArena Spanish | 1228 | 1269 |

## Instruction Following

- Gemma 2 27B: 60.7 (#244)
- Llama-3.3-70B-Instruct: 71.3 (#152)

| Benchmark | Gemma 2 27B | Llama-3.3-70B-Instruct |
|---|---|---|
| LiveBench Instruction Following | 58.1% | 82.7% |
| LMArena Instruction Following | 1206 | 1242 |

## Long Context

- Gemma 2 27B: 37.3 (#213)
- Llama-3.3-70B-Instruct: 26.4 (#290)

| Benchmark | Gemma 2 27B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Longer Query | 1231 | 1256 |
| Fiction.LiveBench | — | 33.3% |

## Writing & Preference

- Gemma 2 27B: 44.4 (#220)
- Llama-3.3-70B-Instruct: 47.8 (#203)

| Benchmark | Gemma 2 27B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Text | 1231 | 1274 |
| LMArena Creative Writing | 1241 | 1250 |
| LMArena Multi-Turn | 1224 | 1279 |
| LiveBench Language | 32.6% | 39.2% |

## FAQ

### Is Gemma 2 27B better than Llama-3.3-70B-Instruct?

Llama-3.3-70B-Instruct is the stronger model overall, scoring 30.3 to 29.2 on the Noometry Index.

### Which is cheaper, Gemma 2 27B or Llama-3.3-70B-Instruct?

Llama-3.3-70B-Instruct is cheaper. It lists at $0.10 per million input tokens and $0.32 per million output tokens; Gemma 2 27B lists at $0.65 and $0.65.

### Is Gemma 2 27B or Llama-3.3-70B-Instruct better for coding?

Gemma 2 27B scores higher on coding benchmarks: 33.5 versus 30.6 in the Noometry coding category.

### Which has the bigger context window?

Llama-3.3-70B-Instruct does, with 128K tokens against 8K.

### How many benchmarks do Gemma 2 27B and Llama-3.3-70B-Instruct share?

34 benchmarks have published results for both models. Gemma 2 27B has 34 scored results on Noometry and Llama-3.3-70B-Instruct has 43.