Model comparison
Llama 2-7B vs o1
o1 is the stronger model overall, scoring 40.9 to 29.1 on the Noometry Index.
Last verified . 17 shared benchmarks.
MetaSummary
- They share 17 benchmarks with published results for both. Llama 2-7B scores higher in 0 categories and o1 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where o1 leads 55.6 to 28.0.
- The biggest single-benchmark swing is Chess Puzzles: 0% for Llama 2-7B and 15% for o1.
- Llama 2-7B has downloadable open weights; the other is API-only.
Side by side
| Llama 2-7B | o1 | |
|---|---|---|
| Provider | Meta | OpenAI |
| Noometry Index | 29.1 | 40.9 |
| Released | 2023-07-18 | 2024-09-12 |
| Weights | Open | Proprietary |
| Context window | — | 200K |
| Max output | — | 100K |
| Input $ / M tokens | — | $15 |
| Output $ / M tokens | — | $60 |
| Results tracked | 29 | 52 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding o1 leads
Llama 2-7B: 29.2 (#307), o1: 46.1 (#70)
| Benchmark | Llama 2-7B | o1 |
|---|---|---|
| LMArena Coding | 1002 | 1367 |
| Aider Polyglot | — | 61.7% |
| WeirdML | — | 47.6% |
| LiveBench Coding | — | 69.7% |
| CadEval | — | 56% |
| HumanEval+ | — | 89% |
| MBPP+ | — | 80.2% |
Agentic & Tool Use Not comparable
Llama 2-7B: —, o1: 24.6 (#117)
| Benchmark | Llama 2-7B | o1 |
|---|---|---|
| Cybench | — | 10% |
| METR Time Horizons | — | 51.1% |
Reasoning o1 leads
Llama 2-7B: 15.7 (#312), o1: 27.9 (#111)
| Benchmark | Llama 2-7B | o1 |
|---|---|---|
| Chess Puzzles | 0% | 15% |
| LMArena Hard Prompts | 1009 | 1371 |
| Epoch Capabilities Index | 99.06 | 141.91 |
| SimpleBench | — | 41.7% |
| ARC-AGI-1 | — | 30.7% |
| EnigmaEval | — | 5.7% |
| LiveBench Reasoning | — | 91.6% |
| DTBench | — | 74.7% |
| LiveBench Data Analysis | — | 65.5% |
| LMCA | — | 22.3% |
| BIG-Bench Hard | 39.2% | — |
| HellaSwag | 77.2% | — |
| LAMBADA | 73.3% | — |
| LiveBench | — | 75.7% |
| PIQA | 78.8% | — |
| WinoGrande | 69.2% | — |
Math o1 leads
Llama 2-7B: 30.7 (#233), o1: 36.1 (#175)
| Benchmark | Llama 2-7B | o1 |
|---|---|---|
| LMArena Math | 1042 | 1388 |
| FrontierMath (Tiers 1-3) | — | 14.7% |
| OTIS Mock AIME 2024-2025 | — | 73.3% |
| LiveBench Math | — | 80.3% |
| MATH Level 5 | — | 94.7% |
| FrontierMath (Feb 2025 set) | — | 9.3% |
| GSM8K | 16.7% | — |
Knowledge o1 leads
Llama 2-7B: 28.2 (#248), o1: 41.5 (#110)
| Benchmark | Llama 2-7B | o1 |
|---|---|---|
| LMArena Expert | 1036 | 1361 |
| GPQA Diamond | — | 76.8% |
| Humanity's Last Exam | — | 8% |
| SimpleQA Verified | — | 41.1% |
| Confabulations | — | 11.7% |
| ARC (AI2) Challenge | 45.9% | — |
| BoolQ | 77.9% | — |
| MMLU | 45.8% | — |
| OpenBookQA | 58.6% | — |
| TriviaQA | 73.7% | — |
Multimodal Not comparable
Llama 2-7B: —, o1: 34.2 (#93)
| Benchmark | Llama 2-7B | o1 |
|---|---|---|
| LMArena Vision | — | 1168 |
| GeoBench | — | 80% |
| VPCT | — | 37% |
| ScienceQA | 43.1% | — |
| SpatialViz-Bench | — | 41.4% |
Multilingual o1 leads
Llama 2-7B: 23.8 (#293), o1: 48.6 (#142)
| Benchmark | Llama 2-7B | o1 |
|---|---|---|
| LMArena Non-English | 973 | 1358 |
| LMArena Chinese | 973 | 1394 |
| LMArena French | 970 | 1344 |
| LMArena German | 978 | 1337 |
| LMArena Russian | 995 | 1356 |
| LMArena Spanish | 1007 | 1345 |
| LMArena Japanese | — | 1346 |
| LMArena Korean | — | 1396 |
Instruction Following o1 leads
Llama 2-7B: 50.8 (#298), o1: 74.8 (#86)
| Benchmark | Llama 2-7B | o1 |
|---|---|---|
| LMArena Instruction Following | 1006 | 1367 |
| LiveBench Instruction Following | — | 81.5% |
Long Context o1 leads
Llama 2-7B: 30.4 (#287), o1: 50.3 (#9)
| Benchmark | Llama 2-7B | o1 |
|---|---|---|
| LMArena Longer Query | 999 | 1378 |
| Fiction.LiveBench | — | 83.3% |
Writing & Preference o1 leads
Llama 2-7B: 28.0 (#298), o1: 55.6 (#144)
| Benchmark | Llama 2-7B | o1 |
|---|---|---|
| LMArena Text | 1053 | 1366 |
| LMArena Creative Writing | 1033 | 1348 |
| LMArena Multi-Turn | 1029 | 1369 |
| Short-Story Creative Writing | — | 70.2% |
| LiveBench Language | — | 65.4% |
Frequently asked questions
Is Llama 2-7B better than o1?
o1 is the stronger model overall, scoring 40.9 to 29.1 on the Noometry Index.
Is Llama 2-7B or o1 better for coding?
o1 scores higher on coding benchmarks: 46.1 versus 29.2 in the Noometry coding category.
How many benchmarks do Llama 2-7B and o1 share?
17 benchmarks have published results for both models. Llama 2-7B has 29 scored results on Noometry and o1 has 52.