Model comparison
Llama 13b vs o3
o3 is the stronger model overall, scoring 47.5 to 24.4 on the Noometry Index.
Last verified . 9 shared benchmarks.
Summary
- They share 9 benchmarks with published results for both. Llama 13b scores higher in 0 categories and o3 in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where o3 leads 63.5 to 13.8.
- Llama 13b has downloadable open weights; the other is API-only.
Side by side
| Llama 13b | o3 | |
|---|---|---|
| Provider | Meta | OpenAI |
| Noometry Index | 24.4 | 47.5 |
| Released | 2023-02-24 | 2025-04-16 |
| Weights | Open | Proprietary |
| Context window | — | 200K |
| Max output | — | 100K |
| Input $ / M tokens | — | $2 |
| Output $ / M tokens | — | $8 |
| Results tracked | 21 | 63 |
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Category by category
Coding o3 leads
Llama 13b: 21.4 (#337), o3: 46.8 (#64)
| Benchmark | Llama 13b | o3 |
|---|---|---|
| LMArena Coding | 683 | 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 Not comparable
Llama 13b: —, o3: 34.5 (#44)
| Benchmark | Llama 13b | o3 |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 63% |
| GDPval | — | 30.8% |
| DeepResearch Bench | — | 45.2% |
| OSWorld | — | 23% |
| LMArena Search | — | 1144 |
| METR Time Horizons | — | 65.4% |
Reasoning o3 leads
Llama 13b: 14.0 (#329), o3: 32.0 (#78)
| Benchmark | Llama 13b | o3 |
|---|---|---|
| LMArena Hard Prompts | 728 | 1402 |
| Epoch Capabilities Index | 100.58 | 146.86 |
| ARC-AGI-2 | — | 6.5% |
| SimpleBench | — | 53.1% |
| Kagi LLM Benchmark | — | 67.6% |
| ARC-AGI-1 | — | 60.8% |
| CritPt | — | 1.4% |
| Chess Puzzles | — | 38% |
| EnigmaEval | — | 13.1% |
| Mystery Game Puzzles | — | 29% |
| DTBench | — | 84.8% |
| LMCA | — | 39.7% |
| BIG-Bench Hard | 37.9% | — |
| ForecastBench | — | 62.5 |
| HellaSwag | 79.2% | — |
| LAMBADA | 75.2% | — |
| PIQA | 80.1% | — |
| WinoGrande | 73% | — |
Math o3 leads
Llama 13b: 26.7 (#256), o3: 50.2 (#58)
| Benchmark | Llama 13b | o3 |
|---|---|---|
| LMArena Math | 838 | 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 | 20.6% | — |
Knowledge Not comparable
Llama 13b: —, o3: 54.6 (#52)
| Benchmark | Llama 13b | o3 |
|---|---|---|
| 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% |
| LMArena Expert | — | 1402 |
| ARC (AI2) Challenge | 52.7% | — |
| BoolQ | 78.7% | — |
| MMLU | 47.7% | — |
| OpenBookQA | 56.4% | — |
| TriviaQA | 77.9% | — |
Multimodal Not comparable
Llama 13b: —, o3: 41.4 (#36)
| Benchmark | Llama 13b | o3 |
|---|---|---|
| LMArena Vision | — | 1214 |
| GeoBench | — | 74% |
| VPCT | — | 52% |
| ScienceQA | 43.3% | — |
Multilingual o3 leads
Llama 13b: 16.6 (#297), o3: 51.7 (#105)
| Benchmark | Llama 13b | o3 |
|---|---|---|
| LMArena Non-English | 819 | 1401 |
| LMArena Chinese | — | 1437 |
| LMArena French | — | 1430 |
| LMArena German | — | 1420 |
| LMArena Japanese | — | 1403 |
| LMArena Korean | — | 1370 |
| LMArena Russian | — | 1406 |
| LMArena Spanish | — | 1395 |
Instruction Following o3 leads
Llama 13b: 36.7 (#305), o3: 72.8 (#127)
| Benchmark | Llama 13b | o3 |
|---|---|---|
| LMArena Instruction Following | 781 | 1368 |
| IFEval | — | 86.9% |
Long Context Not comparable
Llama 13b: —, o3: 53.3 (#6)
| Benchmark | Llama 13b | o3 |
|---|---|---|
| Fiction.LiveBench | — | 88.9% |
| CL-bench | — | 17.8% |
| LMArena Longer Query | — | 1372 |
Writing & Preference o3 leads
Llama 13b: 13.8 (#312), o3: 63.5 (#64)
| Benchmark | Llama 13b | o3 |
|---|---|---|
| LMArena Text | 834 | 1410 |
| LMArena Creative Writing | 794 | 1359 |
| LMArena Multi-Turn | 753 | 1405 |
| Short-Story Creative Writing | — | 83.9% |
| EQ-Bench Creative Writing | — | 1676 |
| WildBench | — | 86.1% |
Frequently asked questions
Is Llama 13b better than o3?
o3 is the stronger model overall, scoring 47.5 to 24.4 on the Noometry Index.
Is Llama 13b or o3 better for coding?
o3 scores higher on coding benchmarks: 46.8 versus 21.4 in the Noometry coding category.
How many benchmarks do Llama 13b and o3 share?
9 benchmarks have published results for both models. Llama 13b has 21 scored results on Noometry and o3 has 63.