Model comparison
Llama 2-7B vs o3-pro
o3-pro is the stronger model overall, scoring 42.9 to 29.1 on the Noometry Index.
Last verified . 1 shared benchmarks.
MetaSummary
- They share 1 benchmark with published results for both. Llama 2-7B scores higher in 0 categories and o3-pro in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in long context, where o3-pro leads 72.2 to 30.4.
- Llama 2-7B has downloadable open weights; the other is API-only.
Side by side
| Llama 2-7B | o3-pro | |
|---|---|---|
| Provider | Meta | OpenAI |
| Noometry Index | 29.1 | 42.9 |
| Released | 2023-07-18 | 2025-06-10 |
| Weights | Open | Proprietary |
| Context window | — | 200K |
| Max output | — | 100K |
| Input $ / M tokens | — | $20 |
| Output $ / M tokens | — | $80 |
| Results tracked | 29 | 12 |
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Category by category
Coding o3-pro leads
Llama 2-7B: 29.2 (#307), o3-pro: 55.5 (#24)
| Benchmark | Llama 2-7B | o3-pro |
|---|---|---|
| Aider Polyglot | — | 84.9% |
| WeirdML | — | 58.2% |
| LMArena Coding | 1002 | — |
Reasoning o3-pro leads
Llama 2-7B: 15.7 (#312), o3-pro: 23.8 (#171)
| Benchmark | Llama 2-7B | o3-pro |
|---|---|---|
| Epoch Capabilities Index | 99.06 | 147.42 |
| ARC-AGI-2 | — | 4.9% |
| Kagi LLM Benchmark | — | 72.1% |
| ARC-AGI-1 | — | 59.3% |
| Chess Puzzles | 0% | — |
| LMArena Hard Prompts | 1009 | — |
| DTBench | — | 86.9% |
| LMCA | — | 38.5% |
| BIG-Bench Hard | 39.2% | — |
| HellaSwag | 77.2% | — |
| LAMBADA | 73.3% | — |
| PIQA | 78.8% | — |
| WinoGrande | 69.2% | — |
Math Not comparable
Llama 2-7B: 30.7 (#233), o3-pro: —
| Benchmark | Llama 2-7B | o3-pro |
|---|---|---|
| LMArena Math | 1042 | — |
| GSM8K | 16.7% | — |
Knowledge o3-pro leads
Llama 2-7B: 28.2 (#248), o3-pro: 29.5 (#238)
| Benchmark | Llama 2-7B | o3-pro |
|---|---|---|
| Confabulations | — | 14.2% |
| Vectara Hallucination Rate | — | 23.3% |
| LMArena Expert | 1036 | — |
| ARC (AI2) Challenge | 45.9% | — |
| BoolQ | 77.9% | — |
| MMLU | 45.8% | — |
| OpenBookQA | 58.6% | — |
| TriviaQA | 73.7% | — |
Multimodal Not comparable
Llama 2-7B: —, o3-pro: —
| Benchmark | Llama 2-7B | o3-pro |
|---|---|---|
| ScienceQA | 43.1% | — |
Multilingual Not comparable
Llama 2-7B: 23.8 (#293), o3-pro: —
| Benchmark | Llama 2-7B | o3-pro |
|---|---|---|
| LMArena Non-English | 973 | — |
| LMArena Chinese | 973 | — |
| LMArena French | 970 | — |
| LMArena German | 978 | — |
| LMArena Russian | 995 | — |
| LMArena Spanish | 1007 | — |
Instruction Following Not comparable
Llama 2-7B: 50.8 (#298), o3-pro: —
| Benchmark | Llama 2-7B | o3-pro |
|---|---|---|
| LMArena Instruction Following | 1006 | — |
Long Context o3-pro leads
Llama 2-7B: 30.4 (#287), o3-pro: 72.2 (#1)
| Benchmark | Llama 2-7B | o3-pro |
|---|---|---|
| Fiction.LiveBench | — | 97.2% |
| LMArena Longer Query | 999 | — |
Writing & Preference o3-pro leads
Llama 2-7B: 28.0 (#298), o3-pro: 57.1 (#133)
| Benchmark | Llama 2-7B | o3-pro |
|---|---|---|
| LMArena Text | 1053 | — |
| LMArena Creative Writing | 1033 | — |
| Short-Story Creative Writing | — | 84.4% |
| LMArena Multi-Turn | 1029 | — |
Frequently asked questions
Is Llama 2-7B better than o3-pro?
o3-pro is the stronger model overall, scoring 42.9 to 29.1 on the Noometry Index.
Is Llama 2-7B or o3-pro better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 29.2 in the Noometry coding category.
How many benchmarks do Llama 2-7B and o3-pro share?
1 benchmark has published results for both models. Llama 2-7B has 29 scored results on Noometry and o3-pro has 12.