# Llama 2-7B vs o3

> o3 is the stronger model overall, scoring 47.4 to 28.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/llama-2-7b-vs-o3
- Last updated: 2026-10-10
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. Llama 2-7B scores higher in 0 categories and o3 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where o3 leads 63.7 to 28.1.
- The biggest single-benchmark swing is Chess Puzzles: 0% for Llama 2-7B and 38% for o3.
- Llama 2-7B has downloadable open weights; the other is API-only.

## Snapshot

| | Llama 2-7B | o3 |
|---|---|---|
| Provider | Meta | OpenAI |
| Noometry Index | 28.6 | 47.4 |
| Rank | 315 | 53 |
| Context | — | 200K |
| Input $/M | — | $2 |
| Output $/M | — | $8 |
| Weights | Open | Proprietary |

## Coding

- Llama 2-7B: 28.7 (#302)
- o3: 47.3 (#57)

| Benchmark | Llama 2-7B | o3 |
|---|---|---|
| LMArena Coding | 1002 | 1408 |
| SWE-bench Verified | — | 62.3% |
| SWE-bench Verified (bash only) | — | 58.4% |
| Aider Polyglot | — | 81.3% |
| GSO | — | 8.8% |
| WeirdML | — | 52.4% |
| CadEval | — | 74% |
| ALE-Bench | — | 933.55 |

## Agentic & Tool Use

- Llama 2-7B: —
- o3: 34.3 (#42)

| Benchmark | Llama 2-7B | o3 |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 63% |
| GDPval | — | 30.8% |
| DeepResearch Bench | — | 45.2% |
| OSWorld | — | 23% |
| LMArena Search | — | 1144 |
| METR Time Horizons | — | 65.4% |

## Reasoning

- Llama 2-7B: 15.1 (#309)
- o3: 32.1 (#66)

| Benchmark | Llama 2-7B | o3 |
|---|---|---|
| Chess Puzzles | 0% | 38% |
| LMArena Hard Prompts | 1009 | 1402 |
| Epoch Capabilities Index | 98.54 | 146.88 |
| ARC-AGI-2 | — | 6.5% |
| SimpleBench | — | 53.1% |
| Kagi LLM Benchmark | — | 67.6% |
| ARC-AGI-1 | — | 60.8% |
| CritPt | — | 1.4% |
| EnigmaEval | — | 13.1% |
| Mystery Game Puzzles | — | 29% |
| DTBench | — | 84.8% |
| LMCA | — | 39.7% |
| BIG-Bench Hard | 39.2% | — |
| ForecastBench | — | 62.5 |
| HellaSwag | 77.2% | — |
| LAMBADA | 73.3% | — |
| PIQA | 78.8% | — |
| WinoGrande | 69.2% | — |

## Math

- Llama 2-7B: 28.2 (#231)
- o3: 48.9 (#49)

| Benchmark | Llama 2-7B | o3 |
|---|---|---|
| LMArena Math | 1042 | 1426 |
| FrontierMath (Tiers 1-3) | — | 33.3% |
| OTIS Mock AIME 2024-2025 | — | 84.4% |
| Omni-MATH | — | 71.4% |
| MATH Level 5 | — | 97.8% |
| FrontierMath (Feb 2025 set) | — | 18.7% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
| GSM8K | 16.7% | — |

## Knowledge

- Llama 2-7B: 27.7 (#243)
- o3: 54.5 (#47)

| Benchmark | Llama 2-7B | o3 |
|---|---|---|
| LMArena Expert | 1036 | 1403 |
| GPQA Diamond | — | 81.8% |
| Humanity's Last Exam | — | 20.3% |
| SimpleQA Verified | — | 49.4% |
| MMLU-Pro | — | 85.9% |
| Confabulations | — | 14.4% |
| GPQA (HELM) | — | 75.3% |
| ARC (AI2) Challenge | 45.9% | — |
| BoolQ | 77.9% | — |
| MMLU | 45.8% | — |
| OpenBookQA | 58.6% | — |
| TriviaQA | 73.7% | — |

## Multimodal

- Llama 2-7B: —
- o3: 40.7 (#35)

| Benchmark | Llama 2-7B | o3 |
|---|---|---|
| LMArena Vision | — | 1214 |
| GeoBench | — | 74% |
| VPCT | — | 52% |
| ScienceQA | 43.1% | — |

## Multilingual

- Llama 2-7B: 23.9 (#288)
- o3: 51.9 (#99)

| Benchmark | Llama 2-7B | o3 |
|---|---|---|
| LMArena Non-English | 973 | 1402 |
| LMArena Chinese | 973 | 1438 |
| LMArena French | 969 | 1430 |
| LMArena German | 978 | 1420 |
| LMArena Russian | 995 | 1407 |
| LMArena Spanish | 1007 | 1395 |
| LMArena Japanese | — | 1404 |
| LMArena Korean | — | 1371 |

## Instruction Following

- Llama 2-7B: 51.0 (#293)
- o3: 73.0 (#122)

| Benchmark | Llama 2-7B | o3 |
|---|---|---|
| LMArena Instruction Following | 1006 | 1368 |
| IFEval | — | 86.9% |

## Long Context

- Llama 2-7B: 30.4 (#282)
- o3: 53.2 (#6)

| Benchmark | Llama 2-7B | o3 |
|---|---|---|
| LMArena Longer Query | 999 | 1372 |
| Fiction.LiveBench | — | 88.9% |
| CL-bench | — | 17.8% |

## Writing & Preference

- Llama 2-7B: 28.1 (#293)
- o3: 63.7 (#62)

| Benchmark | Llama 2-7B | o3 |
|---|---|---|
| LMArena Text | 1053 | 1410 |
| LMArena Creative Writing | 1033 | 1359 |
| LMArena Multi-Turn | 1029 | 1405 |
| Short-Story Creative Writing | — | 83.9% |
| EQ-Bench Creative Writing | — | 1676 |
| WildBench | — | 86.1% |

## FAQ

### Is Llama 2-7B better than o3?

o3 is the stronger model overall, scoring 47.4 to 28.6 on the Noometry Index.

### Is Llama 2-7B or o3 better for coding?

o3 scores higher on coding benchmarks: 47.3 versus 28.7 in the Noometry coding category.

### How many benchmarks do Llama 2-7B and o3 share?

17 benchmarks have published results for both models. Llama 2-7B has 29 scored results on Noometry and o3 has 63.