Model comparison
GPT-4.5 vs Llama 3-70B
GPT-4.5 is the stronger model overall, scoring 37.2 to 28.8 on the Noometry Index.
Last verified . 22 shared benchmarks.
Summary
- They share 22 benchmarks with published results for both. GPT-4.5 scores higher in 8 categories and Llama 3-70B in 1 category; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-4.5 leads 32.6 to 12.8.
- The biggest single-benchmark swing is MATH Level 5: 78.6% for GPT-4.5 and 22.6% for Llama 3-70B.
- Llama 3-70B has downloadable open weights; the other is API-only.
Side by side
| GPT-4.5 | Llama 3-70B | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 37.2 | 28.8 |
| Released | 2025-02-27 | 2024-04-18 |
| Weights | Proprietary | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 42 | 31 |
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Category by category
Coding GPT-4.5 leads
GPT-4.5: 42.2 (#109), Llama 3-70B: 35.8 (#218)
| Benchmark | GPT-4.5 | Llama 3-70B |
|---|---|---|
| LMArena Coding | 1396 | 1206 |
| Aider Polyglot | 44.9% | — |
| WeirdML | 39.4% | — |
| BigCodeBench Instruct | — | 43.6% |
| LiveBench Coding | 75.2% | — |
| BigCodeBench Complete | — | 54.5% |
| HumanEval+ | — | 72% |
| MBPP+ | — | 69% |
Agentic & Tool Use GPT-4.5 leads
GPT-4.5: 27.9 (#97), Llama 3-70B: 21.1 (#139)
| Benchmark | GPT-4.5 | Llama 3-70B |
|---|---|---|
| Cybench | 17.5% | 5% |
Reasoning Llama 3-70B leads
GPT-4.5: 13.9 (#330), Llama 3-70B: 18.0 (#288)
| Benchmark | GPT-4.5 | Llama 3-70B |
|---|---|---|
| LMArena Hard Prompts | 1403 | 1195 |
| Epoch Capabilities Index | 136.74 | 122.93 |
| ForecastBench | 61.7 | 57.1 |
| ARC-AGI-2 | 0.8% | — |
| SimpleBench | 34.5% | — |
| Kagi LLM Benchmark | — | 35.1% |
| ARC-AGI-1 | 10.3% | — |
| EnigmaEval | 3.2% | — |
| LiveBench Reasoning | 71.1% | — |
| DTBench | — | 54.2% |
| LiveBench Data Analysis | 64.3% | — |
| LiveBench | 69% | — |
| WinoGrande | — | 83.5% |
Math GPT-4.5 leads
GPT-4.5: 32.6 (#211), Llama 3-70B: 12.8 (#305)
| Benchmark | GPT-4.5 | Llama 3-70B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 37.8% | 4.3% |
| LMArena Math | 1412 | 1218 |
| MATH Level 5 | 78.6% | 22.6% |
| LiveBench Math | 69.3% | — |
Knowledge GPT-4.5 leads
GPT-4.5: 32.5 (#211), Llama 3-70B: 20.8 (#277)
| Benchmark | GPT-4.5 | Llama 3-70B |
|---|---|---|
| GPQA Diamond | 68.7% | 40.6% |
| LMArena Expert | 1394 | 1149 |
| Humanity's Last Exam | 5.4% | — |
| Confabulations | 13.6% | — |
| MMLU | — | 79.3% |
Multimodal Not comparable
GPT-4.5: 37.6 (#71), Llama 3-70B: —
| Benchmark | GPT-4.5 | Llama 3-70B |
|---|---|---|
| LMArena Vision | 1195 | — |
| VPCT | 45% | — |
Multilingual GPT-4.5 leads
GPT-4.5: 52.5 (#83), Llama 3-70B: 33.6 (#251)
| Benchmark | GPT-4.5 | Llama 3-70B |
|---|---|---|
| LMArena Non-English | 1413 | 1142 |
| LMArena Chinese | 1421 | 1114 |
| LMArena French | 1418 | 1232 |
| LMArena German | 1457 | 1169 |
| LMArena Japanese | 1416 | 1017 |
| LMArena Korean | 1392 | 1017 |
| LMArena Russian | 1419 | 1159 |
| LMArena Spanish | — | 1241 |
Instruction Following GPT-4.5 leads
GPT-4.5: 72.6 (#134), Llama 3-70B: 62.5 (#238)
| Benchmark | GPT-4.5 | Llama 3-70B |
|---|---|---|
| LMArena Instruction Following | 1404 | 1194 |
| LiveBench Instruction Following | 72.3% | — |
Long Context GPT-4.5 leads
GPT-4.5: 40.4 (#155), Llama 3-70B: 35.6 (#240)
| Benchmark | GPT-4.5 | Llama 3-70B |
|---|---|---|
| LMArena Longer Query | 1406 | 1174 |
| Fiction.LiveBench | 63.9% | — |
Writing & Preference GPT-4.5 leads
GPT-4.5: 56.9 (#134), Llama 3-70B: 42.8 (#231)
| Benchmark | GPT-4.5 | Llama 3-70B |
|---|---|---|
| LMArena Text | 1417 | 1221 |
| LMArena Creative Writing | 1394 | 1210 |
| LMArena Multi-Turn | 1444 | 1223 |
| 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 3-70B?
GPT-4.5 is the stronger model overall, scoring 37.2 to 28.8 on the Noometry Index.
Is GPT-4.5 or Llama 3-70B better for coding?
GPT-4.5 scores higher on coding benchmarks: 42.2 versus 35.8 in the Noometry coding category.
How many benchmarks do GPT-4.5 and Llama 3-70B share?
22 benchmarks have published results for both models. GPT-4.5 has 42 scored results on Noometry and Llama 3-70B has 31.