Model comparison
GPT-4.5 vs Llama 2-13B
GPT-4.5 is the stronger model overall, scoring 37.2 to 29.6 on the Noometry Index.
Last verified . 17 shared benchmarks.
MetaSummary
- They share 17 benchmarks with published results for both. GPT-4.5 scores higher in 8 categories and Llama 2-13B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GPT-4.5 leads 56.9 to 29.8.
- Llama 2-13B has downloadable open weights; the other is API-only.
Side by side
| GPT-4.5 | Llama 2-13B | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 37.2 | 29.6 |
| Released | 2025-02-27 | 2023-07-18 |
| Weights | Proprietary | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 42 | 32 |
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Category by category
Coding GPT-4.5 leads
GPT-4.5: 42.2 (#109), Llama 2-13B: 30.9 (#291)
| Benchmark | GPT-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Coding | 1396 | 1062 |
| Aider Polyglot | 44.9% | — |
| WeirdML | 39.4% | — |
| LiveBench Coding | 75.2% | — |
Agentic & Tool Use Not comparable
GPT-4.5: 27.9 (#97), Llama 2-13B: —
| Benchmark | GPT-4.5 | Llama 2-13B |
|---|---|---|
| Cybench | 17.5% | — |
Reasoning GPT-4.5 leads
GPT-4.5: 13.9 (#330), Llama 2-13B: 12.8 (#337)
| Benchmark | GPT-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Hard Prompts | 1403 | 1051 |
| Epoch Capabilities Index | 136.74 | 106.17 |
| ARC-AGI-2 | 0.8% | — |
| SimpleBench | 34.5% | — |
| ARC-AGI-1 | 10.3% | — |
| Chess Puzzles | — | 0% |
| EnigmaEval | 3.2% | — |
| LiveBench Reasoning | 71.1% | — |
| DTBench | — | 42.2% |
| LiveBench Data Analysis | 64.3% | — |
| BIG-Bench Hard | — | 58.2% |
| ForecastBench | 61.7 | — |
| HellaSwag | — | 80.7% |
| LAMBADA | — | 76.5% |
| LiveBench | 69% | — |
| PIQA | — | 80.8% |
| WinoGrande | — | 72.8% |
Math GPT-4.5 leads
GPT-4.5: 32.6 (#211), Llama 2-13B: 31.1 (#229)
| Benchmark | GPT-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Math | 1412 | 1065 |
| OTIS Mock AIME 2024-2025 | 37.8% | — |
| LiveBench Math | 69.3% | — |
| MATH Level 5 | 78.6% | — |
| GSM8K | — | 36.9% |
Knowledge GPT-4.5 leads
GPT-4.5: 32.5 (#211), Llama 2-13B: 28.1 (#249)
| Benchmark | GPT-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Expert | 1394 | 1030 |
| GPQA Diamond | 68.7% | — |
| Humanity's Last Exam | 5.4% | — |
| Confabulations | 13.6% | — |
| ARC (AI2) Challenge | — | 60.3% |
| BoolQ | — | 82.4% |
| MMLU | — | 55.6% |
| OpenBookQA | — | 57% |
| TriviaQA | — | 79.6% |
Multimodal Not comparable
GPT-4.5: 37.6 (#71), Llama 2-13B: —
| Benchmark | GPT-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Vision | 1195 | — |
| VPCT | 45% | — |
| ScienceQA | — | 55.8% |
Multilingual GPT-4.5 leads
GPT-4.5: 52.5 (#83), Llama 2-13B: 26.5 (#279)
| Benchmark | GPT-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Non-English | 1413 | 1024 |
| LMArena Chinese | 1421 | 1001 |
| LMArena French | 1418 | 1044 |
| LMArena German | 1457 | 1009 |
| LMArena Japanese | 1416 | 894 |
| LMArena Korean | 1392 | 953 |
| LMArena Russian | 1419 | 1055 |
| LMArena Spanish | — | 1087 |
Instruction Following GPT-4.5 leads
GPT-4.5: 72.6 (#134), Llama 2-13B: 53.3 (#287)
| Benchmark | GPT-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Instruction Following | 1404 | 1045 |
| LiveBench Instruction Following | 72.3% | — |
Long Context GPT-4.5 leads
GPT-4.5: 40.4 (#155), Llama 2-13B: 32.3 (#269)
| Benchmark | GPT-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Longer Query | 1406 | 1064 |
| Fiction.LiveBench | 63.9% | — |
Writing & Preference GPT-4.5 leads
GPT-4.5: 56.9 (#134), Llama 2-13B: 29.8 (#289)
| Benchmark | GPT-4.5 | Llama 2-13B |
|---|---|---|
| LMArena Text | 1417 | 1084 |
| LMArena Creative Writing | 1394 | 1047 |
| LMArena Multi-Turn | 1444 | 1050 |
| Short-Story Creative Writing | 75.6% | — |
| EQ-Bench Creative Writing | 1258 | — |
| LiveBench Language | 61.5% | — |
Frequently asked questions
Is GPT-4.5 better than Llama 2-13B?
GPT-4.5 is the stronger model overall, scoring 37.2 to 29.6 on the Noometry Index.
Is GPT-4.5 or Llama 2-13B better for coding?
GPT-4.5 scores higher on coding benchmarks: 42.2 versus 30.9 in the Noometry coding category.
How many benchmarks do GPT-4.5 and Llama 2-13B share?
17 benchmarks have published results for both models. GPT-4.5 has 42 scored results on Noometry and Llama 2-13B has 32.