# Llama-3.3-70B-Instruct vs o1-mini

> o1-mini is the stronger model overall, scoring 33.7 to 30.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/llama-3-3-70b-instruct-vs-o1-mini
- Last updated: 2026-10-10
- Shared benchmarks: 31

## Summary

- They share 31 benchmarks with published results for both. Llama-3.3-70B-Instruct scores higher in 3 categories and o1-mini in 6 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where o1-mini leads 33.7 to 14.3.
- The biggest single-benchmark swing is MATH Level 5: 41.6% for Llama-3.3-70B-Instruct and 89.2% for o1-mini.
- Llama-3.3-70B-Instruct has downloadable open weights; the other is API-only.

## Snapshot

| | Llama-3.3-70B-Instruct | o1-mini |
|---|---|---|
| Provider | Meta | OpenAI |
| Noometry Index | 30.3 | 33.7 |
| Rank | 283 | 230 |
| Context | 128K | — |
| Input $/M | $0.10 | — |
| Output $/M | $0.32 | — |
| Weights | Open | Proprietary |

## Coding

- Llama-3.3-70B-Instruct: 30.6 (#284)
- o1-mini: 35.1 (#218)

| Benchmark | Llama-3.3-70B-Instruct | o1-mini |
|---|---|---|
| WeirdML | 14.4% | 36.3% |
| LiveBench Coding | 36.6% | 48% |
| LMArena Coding | 1268 | 1362 |
| Aider Polyglot | — | 32.9% |
| SciCode | 26% | — |
| BigCodeBench Instruct | 46.9% | — |
| BigCodeBench Complete | 57.5% | — |
| HumanEval+ | — | 89% |
| MBPP+ | — | 78.8% |

## Agentic & Tool Use

- Llama-3.3-70B-Instruct: 25.6 (#100)
- o1-mini: 24.3 (#112)

| Benchmark | Llama-3.3-70B-Instruct | o1-mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | 31.9% | — |
| Cybench | — | 10% |
| BALROG | 23% | — |

## Reasoning

- Llama-3.3-70B-Instruct: 13.7 (#325)
- o1-mini: 8.9 (#340)

| Benchmark | Llama-3.3-70B-Instruct | o1-mini |
|---|---|---|
| SimpleBench | 19.9% | 18.1% |
| LiveBench Reasoning | 50.8% | 72.3% |
| LMArena Hard Prompts | 1257 | 1333 |
| LiveBench Data Analysis | 49.5% | 57.9% |
| Epoch Capabilities Index | 127.32 | 135.82 |
| LiveBench | 50.2% | 57.8% |
| ARC-AGI-2 | — | 0.8% |
| ARC-AGI-1 | — | 14% |
| CritPt | 0% | — |
| DTBench | 59.5% | — |
| LMCA | 17.5% | — |
| ForecastBench | 58.6 | — |

## Math

- Llama-3.3-70B-Instruct: 14.3 (#292)
- o1-mini: 33.7 (#168)

| Benchmark | Llama-3.3-70B-Instruct | o1-mini |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 5.1% | 46.9% |
| LiveBench Math | 42.2% | 62% |
| LMArena Math | 1268 | 1358 |
| MATH Level 5 | 41.6% | 89.2% |
| FrontierMath (Feb 2025 set) | — | 1.7% |

## Knowledge

- Llama-3.3-70B-Instruct: 30.5 (#220)
- o1-mini: 34.8 (#180)

| Benchmark | Llama-3.3-70B-Instruct | o1-mini |
|---|---|---|
| GPQA Diamond | 47.4% | 62.4% |
| Confabulations | 22.8% | 18.6% |
| LMArena Expert | 1225 | 1316 |
| Vectara Hallucination Rate | 4.1% | — |
| MMLU | 86.3% | — |

## Multilingual

- Llama-3.3-70B-Instruct: 40.1 (#215)
- o1-mini: 43.8 (#177)

| Benchmark | Llama-3.3-70B-Instruct | o1-mini |
|---|---|---|
| LMArena Non-English | 1236 | 1289 |
| LMArena Chinese | 1217 | 1314 |
| LMArena French | 1280 | 1292 |
| LMArena German | 1251 | 1278 |
| LMArena Japanese | 1149 | 1245 |
| LMArena Korean | 1142 | 1223 |
| LMArena Russian | 1252 | 1283 |
| LMArena Spanish | 1269 | 1302 |

## Instruction Following

- Llama-3.3-70B-Instruct: 71.3 (#152)
- o1-mini: 67.0 (#200)

| Benchmark | Llama-3.3-70B-Instruct | o1-mini |
|---|---|---|
| LiveBench Instruction Following | 82.7% | 65.4% |
| LMArena Instruction Following | 1242 | 1304 |

## Long Context

- Llama-3.3-70B-Instruct: 26.4 (#290)
- o1-mini: 40.1 (#156)

| Benchmark | Llama-3.3-70B-Instruct | o1-mini |
|---|---|---|
| LMArena Longer Query | 1256 | 1321 |
| Fiction.LiveBench | 33.3% | — |

## Writing & Preference

- Llama-3.3-70B-Instruct: 47.8 (#203)
- o1-mini: 48.6 (#196)

| Benchmark | Llama-3.3-70B-Instruct | o1-mini |
|---|---|---|
| LMArena Text | 1274 | 1317 |
| LMArena Creative Writing | 1250 | 1244 |
| LMArena Multi-Turn | 1279 | 1314 |
| LiveBench Language | 39.2% | 40.9% |
| Short-Story Creative Writing | — | 64.9% |

## FAQ

### Is Llama-3.3-70B-Instruct better than o1-mini?

o1-mini is the stronger model overall, scoring 33.7 to 30.3 on the Noometry Index.

### Is Llama-3.3-70B-Instruct or o1-mini better for coding?

o1-mini scores higher on coding benchmarks: 35.1 versus 30.6 in the Noometry coding category.

### How many benchmarks do Llama-3.3-70B-Instruct and o1-mini share?

31 benchmarks have published results for both models. Llama-3.3-70B-Instruct has 43 scored results on Noometry and o1-mini has 39.