Model comparison
Llama 3-8B vs o3-pro
o3-pro is the stronger model overall, scoring 42.9 to 25.5 on the Noometry Index.
Last verified . 2 shared benchmarks.
MetaSummary
- They share 2 benchmarks with published results for both. Llama 3-8B 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 34.2.
- The biggest single-benchmark swing is DTBench: 43.9% for Llama 3-8B and 86.9% for o3-pro.
- Llama 3-8B has downloadable open weights; the other is API-only.
Side by side
| Llama 3-8B | o3-pro | |
|---|---|---|
| Provider | Meta | OpenAI |
| Noometry Index | 25.5 | 42.9 |
| Released | 2024-04-18 | 2025-06-10 |
| Weights | Open | Proprietary |
| Context window | — | 200K |
| Max output | — | 100K |
| Input $ / M tokens | — | $20 |
| Output $ / M tokens | — | $80 |
| Results tracked | 34 | 12 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding o3-pro leads
Llama 3-8B: 31.0 (#289), o3-pro: 55.5 (#24)
| Benchmark | Llama 3-8B | o3-pro |
|---|---|---|
| Aider Polyglot | — | 84.9% |
| WeirdML | — | 58.2% |
| BigCodeBench Instruct | 31.9% | — |
| LMArena Coding | 1152 | — |
| BigCodeBench Complete | 36.9% | — |
| HumanEval+ | 56.7% | — |
| MBPP+ | 54.8% | — |
Reasoning o3-pro leads
Llama 3-8B: 14.3 (#326), o3-pro: 23.8 (#171)
| Benchmark | Llama 3-8B | o3-pro |
|---|---|---|
| DTBench | 43.9% | 86.9% |
| Epoch Capabilities Index | 116.45 | 147.42 |
| ARC-AGI-2 | — | 4.9% |
| Kagi LLM Benchmark | — | 72.1% |
| ARC-AGI-1 | — | 59.3% |
| Chess Puzzles | 0% | — |
| LMArena Hard Prompts | 1133 | — |
| LMCA | — | 38.5% |
| Adversarial NLI | 57.3% | — |
| ForecastBench | 58.6 | — |
| WinoGrande | 75.7% | — |
Math Not comparable
Llama 3-8B: 8.8 (#323), o3-pro: —
| Benchmark | Llama 3-8B | o3-pro |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.9% | — |
| LMArena Math | 1151 | — |
| MATH Level 5 | 6.1% | — |
Knowledge o3-pro leads
Llama 3-8B: 7.8 (#308), o3-pro: 29.5 (#238)
| Benchmark | Llama 3-8B | o3-pro |
|---|---|---|
| GPQA Diamond | 26.1% | — |
| Confabulations | — | 14.2% |
| Vectara Hallucination Rate | — | 23.3% |
| LMArena Expert | 1113 | — |
| ARC (AI2) Challenge | 82.8% | — |
| MMLU | 68.8% | — |
| OpenBookQA | 82.6% | — |
| TriviaQA | 67.7% | — |
Multilingual Not comparable
Llama 3-8B: 30.8 (#261), o3-pro: —
| Benchmark | Llama 3-8B | o3-pro |
|---|---|---|
| LMArena Non-English | 1098 | — |
| LMArena Chinese | 1076 | — |
| LMArena French | 1159 | — |
| LMArena German | 1104 | — |
| LMArena Japanese | 967 | — |
| LMArena Korean | 1004 | — |
| LMArena Russian | 1109 | — |
| LMArena Spanish | 1173 | — |
Instruction Following Not comparable
Llama 3-8B: 58.4 (#260), o3-pro: —
| Benchmark | Llama 3-8B | o3-pro |
|---|---|---|
| LMArena Instruction Following | 1127 | — |
Long Context o3-pro leads
Llama 3-8B: 34.2 (#251), o3-pro: 72.2 (#1)
| Benchmark | Llama 3-8B | o3-pro |
|---|---|---|
| Fiction.LiveBench | — | 97.2% |
| LMArena Longer Query | 1128 | — |
Writing & Preference o3-pro leads
Llama 3-8B: 37.5 (#256), o3-pro: 57.1 (#133)
| Benchmark | Llama 3-8B | o3-pro |
|---|---|---|
| LMArena Text | 1166 | — |
| LMArena Creative Writing | 1150 | — |
| Short-Story Creative Writing | — | 84.4% |
| LMArena Multi-Turn | 1152 | — |
Frequently asked questions
Is Llama 3-8B better than o3-pro?
o3-pro is the stronger model overall, scoring 42.9 to 25.5 on the Noometry Index.
Is Llama 3-8B or o3-pro better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 31.0 in the Noometry coding category.
How many benchmarks do Llama 3-8B and o3-pro share?
2 benchmarks have published results for both models. Llama 3-8B has 34 scored results on Noometry and o3-pro has 12.