# Llama 2-7B vs Llama-3.3-70B-Instruct

> Llama-3.3-70B-Instruct is the stronger model overall, scoring 30.3 to 28.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/llama-2-7b-vs-llama-3-3-70b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. Llama 2-7B 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 instruction following, where Llama-3.3-70B-Instruct leads 71.3 to 51.0.

## Snapshot

| | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| Provider | Meta | Meta |
| Noometry Index | 28.6 | 30.3 |
| Rank | 315 | 283 |
| Context | — | 128K |
| Input $/M | — | $0.10 |
| Output $/M | — | $0.32 |
| Weights | Open | Open |

## Coding

- Llama 2-7B: 28.7 (#302)
- Llama-3.3-70B-Instruct: 30.6 (#284)

| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Coding | 1002 | 1268 |
| SciCode | — | 26% |
| WeirdML | — | 14.4% |
| BigCodeBench Instruct | — | 46.9% |
| LiveBench Coding | — | 36.6% |
| BigCodeBench Complete | — | 57.5% |

## Agentic & Tool Use

- Llama 2-7B: —
- Llama-3.3-70B-Instruct: 25.6 (#100)

| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 31.9% |
| BALROG | — | 23% |

## Reasoning

- Llama 2-7B: 15.1 (#309)
- Llama-3.3-70B-Instruct: 13.7 (#325)

| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Hard Prompts | 1009 | 1257 |
| Epoch Capabilities Index | 98.54 | 127.32 |
| SimpleBench | — | 19.9% |
| CritPt | — | 0% |
| Chess Puzzles | 0% | — |
| LiveBench Reasoning | — | 50.8% |
| DTBench | — | 59.5% |
| LiveBench Data Analysis | — | 49.5% |
| LMCA | — | 17.5% |
| BIG-Bench Hard | 39.2% | — |
| ForecastBench | — | 58.6 |
| HellaSwag | 77.2% | — |
| LAMBADA | 73.3% | — |
| LiveBench | — | 50.2% |
| PIQA | 78.8% | — |
| WinoGrande | 69.2% | — |

## Math

- Llama 2-7B: 28.2 (#231)
- Llama-3.3-70B-Instruct: 14.3 (#292)

| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Math | 1042 | 1268 |
| OTIS Mock AIME 2024-2025 | — | 5.1% |
| LiveBench Math | — | 42.2% |
| MATH Level 5 | — | 41.6% |
| GSM8K | 16.7% | — |

## Knowledge

- Llama 2-7B: 27.7 (#243)
- Llama-3.3-70B-Instruct: 30.5 (#220)

| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Expert | 1036 | 1225 |
| MMLU | 45.8% | 86.3% |
| GPQA Diamond | — | 47.4% |
| Confabulations | — | 22.8% |
| Vectara Hallucination Rate | — | 4.1% |
| ARC (AI2) Challenge | 45.9% | — |
| BoolQ | 77.9% | — |
| OpenBookQA | 58.6% | — |
| TriviaQA | 73.7% | — |

## Multimodal

- Llama 2-7B: —
- Llama-3.3-70B-Instruct: —

| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| ScienceQA | 43.1% | — |

## Multilingual

- Llama 2-7B: 23.9 (#288)
- Llama-3.3-70B-Instruct: 40.1 (#215)

| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Non-English | 973 | 1236 |
| LMArena Chinese | 973 | 1217 |
| LMArena French | 969 | 1280 |
| LMArena German | 978 | 1251 |
| LMArena Russian | 995 | 1252 |
| LMArena Spanish | 1007 | 1269 |
| LMArena Japanese | — | 1149 |
| LMArena Korean | — | 1142 |

## Instruction Following

- Llama 2-7B: 51.0 (#293)
- Llama-3.3-70B-Instruct: 71.3 (#152)

| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Instruction Following | 1006 | 1242 |
| LiveBench Instruction Following | — | 82.7% |

## Long Context

- Llama 2-7B: 30.4 (#282)
- Llama-3.3-70B-Instruct: 26.4 (#290)

| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Longer Query | 999 | 1256 |
| Fiction.LiveBench | — | 33.3% |

## Writing & Preference

- Llama 2-7B: 28.1 (#293)
- Llama-3.3-70B-Instruct: 47.8 (#203)

| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Text | 1053 | 1274 |
| LMArena Creative Writing | 1033 | 1250 |
| LMArena Multi-Turn | 1029 | 1279 |
| LiveBench Language | — | 39.2% |

## FAQ

### Is Llama 2-7B better than Llama-3.3-70B-Instruct?

Llama-3.3-70B-Instruct is the stronger model overall, scoring 30.3 to 28.6 on the Noometry Index.

### Is Llama 2-7B or Llama-3.3-70B-Instruct better for coding?

Llama-3.3-70B-Instruct scores higher on coding benchmarks: 30.6 versus 28.7 in the Noometry coding category.

### How many benchmarks do Llama 2-7B and Llama-3.3-70B-Instruct share?

17 benchmarks have published results for both models. Llama 2-7B has 29 scored results on Noometry and Llama-3.3-70B-Instruct has 43.