Model comparison
Llama 13b vs o3-pro
o3-pro is the stronger model overall, scoring 42.9 to 24.4 on the Noometry Index.
Last verified . 1 shared benchmarks.
MetaSummary
- They share 1 benchmark with published results for both. Llama 13b scores higher in 0 categories and o3-pro in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where o3-pro leads 57.1 to 13.8.
- Llama 13b has downloadable open weights; the other is API-only.
Side by side
| Llama 13b | o3-pro | |
|---|---|---|
| Provider | Meta | OpenAI |
| Noometry Index | 24.4 | 42.9 |
| Released | 2023-02-24 | 2025-06-10 |
| Weights | Open | Proprietary |
| Context window | — | 200K |
| Max output | — | 100K |
| Input $ / M tokens | — | $20 |
| Output $ / M tokens | — | $80 |
| Results tracked | 21 | 12 |
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Category by category
Coding o3-pro leads
Llama 13b: 21.4 (#337), o3-pro: 55.5 (#24)
| Benchmark | Llama 13b | o3-pro |
|---|---|---|
| Aider Polyglot | — | 84.9% |
| WeirdML | — | 58.2% |
| LMArena Coding | 683 | — |
Reasoning o3-pro leads
Llama 13b: 14.0 (#329), o3-pro: 23.8 (#171)
| Benchmark | Llama 13b | o3-pro |
|---|---|---|
| Epoch Capabilities Index | 100.58 | 147.42 |
| ARC-AGI-2 | — | 4.9% |
| Kagi LLM Benchmark | — | 72.1% |
| ARC-AGI-1 | — | 59.3% |
| LMArena Hard Prompts | 728 | — |
| DTBench | — | 86.9% |
| LMCA | — | 38.5% |
| BIG-Bench Hard | 37.9% | — |
| HellaSwag | 79.2% | — |
| LAMBADA | 75.2% | — |
| PIQA | 80.1% | — |
| WinoGrande | 73% | — |
Math Not comparable
Llama 13b: 26.7 (#256), o3-pro: —
| Benchmark | Llama 13b | o3-pro |
|---|---|---|
| LMArena Math | 838 | — |
| GSM8K | 20.6% | — |
Knowledge Not comparable
Llama 13b: —, o3-pro: 29.5 (#238)
| Benchmark | Llama 13b | o3-pro |
|---|---|---|
| Confabulations | — | 14.2% |
| Vectara Hallucination Rate | — | 23.3% |
| ARC (AI2) Challenge | 52.7% | — |
| BoolQ | 78.7% | — |
| MMLU | 47.7% | — |
| OpenBookQA | 56.4% | — |
| TriviaQA | 77.9% | — |
Multimodal Not comparable
Llama 13b: —, o3-pro: —
| Benchmark | Llama 13b | o3-pro |
|---|---|---|
| ScienceQA | 43.3% | — |
Multilingual Not comparable
Llama 13b: 16.6 (#297), o3-pro: —
| Benchmark | Llama 13b | o3-pro |
|---|---|---|
| LMArena Non-English | 819 | — |
Instruction Following Not comparable
Llama 13b: 36.7 (#305), o3-pro: —
| Benchmark | Llama 13b | o3-pro |
|---|---|---|
| LMArena Instruction Following | 781 | — |
Long Context Not comparable
Llama 13b: —, o3-pro: 72.2 (#1)
| Benchmark | Llama 13b | o3-pro |
|---|---|---|
| Fiction.LiveBench | — | 97.2% |
Writing & Preference o3-pro leads
Llama 13b: 13.8 (#312), o3-pro: 57.1 (#133)
| Benchmark | Llama 13b | o3-pro |
|---|---|---|
| LMArena Text | 834 | — |
| LMArena Creative Writing | 794 | — |
| Short-Story Creative Writing | — | 84.4% |
| LMArena Multi-Turn | 753 | — |
Frequently asked questions
Is Llama 13b better than o3-pro?
o3-pro is the stronger model overall, scoring 42.9 to 24.4 on the Noometry Index.
Is Llama 13b or o3-pro better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 21.4 in the Noometry coding category.
How many benchmarks do Llama 13b and o3-pro share?
1 benchmark has published results for both models. Llama 13b has 21 scored results on Noometry and o3-pro has 12.