Model comparison
GPT-5 Pro vs Llama 3.1 Nemotron 70b Instruct
GPT-5 Pro is the stronger model overall, scoring 46.4 to 37.6 on the Noometry Index.
Last verified . 0 shared benchmarks.
NVIDIASummary
- The widest gap is in knowledge, where GPT-5 Pro leads 56.7 to 34.1.
- Llama 3.1 Nemotron 70b Instruct has downloadable open weights; the other is API-only.
Side by side
| GPT-5 Pro | Llama 3.1 Nemotron 70b Instruct | |
|---|---|---|
| Provider | OpenAI | NVIDIA |
| Noometry Index | 46.4 | 37.6 |
| Released | 2025-10-06 | 2024-12-18 |
| Weights | Proprietary | Open |
| Context window | 400K | — |
| Max output | 272K | — |
| Input $ / M tokens | $15 | — |
| Output $ / M tokens | $120 | — |
| Results tracked | 12 | 14 |
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Category by category
Coding GPT-5 Pro leads
GPT-5 Pro: 44.0 (#80), Llama 3.1 Nemotron 70b Instruct: 35.9 (#216)
| Benchmark | GPT-5 Pro | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| WeirdML | 60.4% | — |
| BigCodeBench Instruct | — | 38.7% |
| LMArena Coding | — | 1272 |
| BigCodeBench Complete | — | 48.2% |
| AlgoTune | 1.31 | — |
Reasoning GPT-5 Pro leads
GPT-5 Pro: 38.9 (#62), Llama 3.1 Nemotron 70b Instruct: 25.0 (#152)
| Benchmark | GPT-5 Pro | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| ARC-AGI-2 | 18.3% | — |
| SimpleBench | 61.6% | — |
| Kagi LLM Benchmark | 76.8% | — |
| ARC-AGI-1 | 70.2% | — |
| EnigmaEval | 18.8% | — |
| LMArena Hard Prompts | — | 1266 |
| Epoch Capabilities Index | 150.28 | — |
Math GPT-5 Pro leads
GPT-5 Pro: 48.5 (#63), Llama 3.1 Nemotron 70b Instruct: 35.5 (#182)
| Benchmark | GPT-5 Pro | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| FrontierMath (Tiers 1-3) | 55.8% | — |
| FrontierMath Tier 4 | 19.5% | — |
| LMArena Math | — | 1271 |
| FrontierMath Tier 4 (v1) | 14.6% | — |
Knowledge GPT-5 Pro leads
GPT-5 Pro: 56.7 (#42), Llama 3.1 Nemotron 70b Instruct: 34.1 (#199)
| Benchmark | GPT-5 Pro | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| Humanity's Last Exam | 31.6% | — |
| LMArena Expert | — | 1242 |
Multilingual Not comparable
GPT-5 Pro: —, Llama 3.1 Nemotron 70b Instruct: 40.5 (#217)
| Benchmark | GPT-5 Pro | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Non-English | — | 1245 |
| LMArena Chinese | — | 1263 |
| LMArena Russian | — | 1227 |
Instruction Following Not comparable
GPT-5 Pro: —, Llama 3.1 Nemotron 70b Instruct: 65.9 (#213)
| Benchmark | GPT-5 Pro | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Instruction Following | — | 1252 |
Long Context Not comparable
GPT-5 Pro: —, Llama 3.1 Nemotron 70b Instruct: 37.6 (#215)
| Benchmark | GPT-5 Pro | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Longer Query | — | 1238 |
Writing & Preference Not comparable
GPT-5 Pro: —, Llama 3.1 Nemotron 70b Instruct: 48.4 (#203)
| Benchmark | GPT-5 Pro | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Text | — | 1283 |
| LMArena Creative Writing | — | 1269 |
| LMArena Multi-Turn | — | 1275 |
Frequently asked questions
Is GPT-5 Pro better than Llama 3.1 Nemotron 70b Instruct?
GPT-5 Pro is the stronger model overall, scoring 46.4 to 37.6 on the Noometry Index.
Is GPT-5 Pro or Llama 3.1 Nemotron 70b Instruct better for coding?
GPT-5 Pro scores higher on coding benchmarks: 44.0 versus 35.9 in the Noometry coding category.
How many benchmarks do GPT-5 Pro and Llama 3.1 Nemotron 70b Instruct share?
0 benchmarks have published results for both models. GPT-5 Pro has 12 scored results on Noometry and Llama 3.1 Nemotron 70b Instruct has 14.