Model comparison
Llama 3.1 Nemotron 70b Instruct vs o4-mini
o4-mini is the stronger model overall, scoring 41.6 to 37.0 on the Noometry Index.
Last verified . 12 shared benchmarks.
NVIDIASummary
- They share 12 benchmarks with published results for both. Llama 3.1 Nemotron 70b Instruct scores higher in 0 categories and o4-mini in 8 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where o4-mini leads 43.5 to 33.5.
- Llama 3.1 Nemotron 70b Instruct has downloadable open weights; the other is API-only.
Side by side
| Llama 3.1 Nemotron 70b Instruct | o4-mini | |
|---|---|---|
| Provider | NVIDIA | OpenAI |
| Noometry Index | 37.0 | 41.6 |
| Released | 2024-12-18 | 2025-04-16 |
| Weights | Open | Proprietary |
| Context window | — | 200K |
| Max output | — | 100K |
| Input $ / M tokens | — | $1.10 |
| Output $ / M tokens | — | $4.40 |
| Results tracked | 14 | 60 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding o4-mini leads
Llama 3.1 Nemotron 70b Instruct: 35.3 (#212), o4-mini: 41.6 (#110)
| Benchmark | Llama 3.1 Nemotron 70b Instruct | o4-mini |
|---|---|---|
| LMArena Coding | 1272 | 1369 |
| SWE-bench Verified (bash only) | — | 45% |
| Aider Polyglot | — | 72% |
| GSO | — | 3.6% |
| WeirdML | — | 52.6% |
| BigCodeBench Instruct | 38.7% | — |
| BigCodeBench Complete | 48.2% | — |
| CadEval | — | 62% |
| ALE-Bench | — | 826.17 |
| AlgoTune | — | 1.72 |
Agentic & Tool Use Not comparable
Llama 3.1 Nemotron 70b Instruct: —, o4-mini: 32.3 (#57)
| Benchmark | Llama 3.1 Nemotron 70b Instruct | o4-mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 53.2% |
| GDPval | — | 25.3% |
| METR Time Horizons | — | 63.9% |
Reasoning Too close to call
Llama 3.1 Nemotron 70b Instruct: 24.0 (#156), o4-mini: 24.6 (#143)
| Benchmark | Llama 3.1 Nemotron 70b Instruct | o4-mini |
|---|---|---|
| LMArena Hard Prompts | 1266 | 1351 |
| ARC-AGI-2 | — | 6.1% |
| SimpleBench | — | 38.7% |
| Kagi LLM Benchmark | — | 67.6% |
| ARC-AGI-1 | — | 58.7% |
| CritPt | — | 0.6% |
| Chess Puzzles | — | 26% |
| EnigmaEval | — | 9.2% |
| Mystery Game Puzzles | — | 5% |
| DTBench | — | 77.6% |
| LMCA | — | 26.5% |
| Epoch Capabilities Index | — | 145.63 |
| ForecastBench | — | 61.8 |
Math o4-mini leads
Llama 3.1 Nemotron 70b Instruct: 32.9 (#182), o4-mini: 40.2 (#79)
| Benchmark | Llama 3.1 Nemotron 70b Instruct | o4-mini |
|---|---|---|
| LMArena Math | 1271 | 1390 |
| FrontierMath (Tiers 1-3) | — | 36.1% |
| FrontierMath Tier 4 | — | 4.9% |
| OTIS Mock AIME 2024-2025 | — | 81.7% |
| Omni-MATH | — | 72% |
| MATH Level 5 | — | 97.8% |
| FrontierMath (Feb 2025 set) | — | 24.8% |
| FrontierMath Tier 4 (v1) | — | 6.3% |
Knowledge o4-mini leads
Llama 3.1 Nemotron 70b Instruct: 33.5 (#194), o4-mini: 43.5 (#83)
| Benchmark | Llama 3.1 Nemotron 70b Instruct | o4-mini |
|---|---|---|
| LMArena Expert | 1242 | 1344 |
| GPQA Diamond | — | 79.6% |
| Humanity's Last Exam | — | 18.1% |
| SimpleQA Verified | — | 19.6% |
| MMLU-Pro | — | 82% |
| Confabulations | — | 15.8% |
| Vectara Hallucination Rate | — | 18.6% |
| GPQA (HELM) | — | 73.5% |
Multimodal Not comparable
Llama 3.1 Nemotron 70b Instruct: —, o4-mini: 39.5 (#46)
| Benchmark | Llama 3.1 Nemotron 70b Instruct | o4-mini |
|---|---|---|
| LMArena Vision | — | 1194 |
| GeoBench | — | 64% |
| VPCT | — | 57.5% |
Multilingual o4-mini leads
Llama 3.1 Nemotron 70b Instruct: 40.7 (#212), o4-mini: 47.2 (#149)
| Benchmark | Llama 3.1 Nemotron 70b Instruct | o4-mini |
|---|---|---|
| LMArena Non-English | 1245 | 1336 |
| LMArena Chinese | 1263 | 1355 |
| LMArena Russian | 1227 | 1334 |
| LMArena French | — | 1362 |
| LMArena German | — | 1336 |
| LMArena Japanese | — | 1308 |
| LMArena Korean | — | 1313 |
| LMArena Spanish | — | 1346 |
Instruction Following o4-mini leads
Llama 3.1 Nemotron 70b Instruct: 66.2 (#208), o4-mini: 75.4 (#63)
| Benchmark | Llama 3.1 Nemotron 70b Instruct | o4-mini |
|---|---|---|
| LMArena Instruction Following | 1252 | 1321 |
| IFEval | — | 92.8% |
Long Context o4-mini leads
Llama 3.1 Nemotron 70b Instruct: 37.5 (#210), o4-mini: 45.5 (#31)
| Benchmark | Llama 3.1 Nemotron 70b Instruct | o4-mini |
|---|---|---|
| LMArena Longer Query | 1239 | 1315 |
| Fiction.LiveBench | — | 77.8% |
Writing & Preference o4-mini leads
Llama 3.1 Nemotron 70b Instruct: 48.6 (#197), o4-mini: 54.2 (#148)
| Benchmark | Llama 3.1 Nemotron 70b Instruct | o4-mini |
|---|---|---|
| LMArena Text | 1283 | 1353 |
| LMArena Creative Writing | 1269 | 1294 |
| LMArena Multi-Turn | 1275 | 1350 |
| Short-Story Creative Writing | — | 75% |
| WildBench | — | 85.4% |
Frequently asked questions
Is Llama 3.1 Nemotron 70b Instruct better than o4-mini?
o4-mini is the stronger model overall, scoring 41.6 to 37.0 on the Noometry Index.
Is Llama 3.1 Nemotron 70b Instruct or o4-mini better for coding?
o4-mini scores higher on coding benchmarks: 41.6 versus 35.3 in the Noometry coding category.
How many benchmarks do Llama 3.1 Nemotron 70b Instruct and o4-mini share?
12 benchmarks have published results for both models. Llama 3.1 Nemotron 70b Instruct has 14 scored results on Noometry and o4-mini has 60.