# Llama 3.1-70B vs MiMo-V2-Pro

> MiMo-V2-Pro is the stronger model overall, scoring 42.4 to 29.4 on the Noometry Index.

- Canonical page: https://noometry.com/compare/llama-3-1-70b-vs-mimo-v2-pro
- Last updated: 2026-10-10
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. Llama 3.1-70B scores higher in 0 categories and MiMo-V2-Pro in 8 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiMo-V2-Pro leads 62.9 to 35.6.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $0.43 / $0.87 for MiMo-V2-Pro.
- MiMo-V2-Pro accepts more context: 1.05M tokens versus 128K.
- Llama 3.1-70B has downloadable open weights; the other is API-only.

## Snapshot

| | Llama 3.1-70B | MiMo-V2-Pro |
|---|---|---|
| Provider | Meta | Xiaomi |
| Noometry Index | 29.4 | 42.4 |
| Rank | 299 | 102 |
| Context | 128K | 1.05M |
| Input $/M | $0.40 | $0.43 |
| Output $/M | $0.40 | $0.87 |
| Weights | Open | Proprietary |

## Coding

- Llama 3.1-70B: 29.8 (#292)
- MiMo-V2-Pro: 43.4 (#76)

| Benchmark | Llama 3.1-70B | MiMo-V2-Pro |
|---|---|---|
| LMArena Coding | 1260 | 1476 |
| LMArena WebDev | — | 1433 |
| WeirdML | 9% | — |
| BigCodeBench Instruct | 46.1% | — |
| BigCodeBench Complete | 54.8% | — |
| ALE-Bench | — | 785.17 |

## Agentic & Tool Use

- Llama 3.1-70B: 24.9 (#104)
- MiMo-V2-Pro: —

| Benchmark | Llama 3.1-70B | MiMo-V2-Pro |
|---|---|---|
| TheAgentCompany | 6.9% | — |
| BALROG | 27.9% | — |

## Reasoning

- Llama 3.1-70B: 20.8 (#215)
- MiMo-V2-Pro: 21.3 (#200)

| Benchmark | Llama 3.1-70B | MiMo-V2-Pro |
|---|---|---|
| LMArena Hard Prompts | 1241 | 1457 |
| NYT Connections (extended) | — | 25.8% |
| Thematic Generalization | — | 45.9% |
| DTBench | 60% | — |
| LMCA | 14.8% | — |
| Epoch Capabilities Index | 125.91 | — |

## Math

- Llama 3.1-70B: 12.7 (#298)
- MiMo-V2-Pro: 36.7 (#104)

| Benchmark | Llama 3.1-70B | MiMo-V2-Pro |
|---|---|---|
| LMArena Math | 1252 | 1447 |
| OTIS Mock AIME 2024-2025 | 3.6% | — |
| Omni-MATH | 21% | — |
| MATH Level 5 | 36.7% | — |

## Knowledge

- Llama 3.1-70B: 24.1 (#264)
- MiMo-V2-Pro: 40.8 (#106)

| Benchmark | Llama 3.1-70B | MiMo-V2-Pro |
|---|---|---|
| LMArena Expert | 1209 | 1479 |
| GPQA Diamond | 44.2% | — |
| MMLU-Pro | 65.3% | — |
| GPQA (HELM) | 42.6% | — |
| MMLU | 80.1% | — |

## Multilingual

- Llama 3.1-70B: 38.9 (#220)
- MiMo-V2-Pro: 52.9 (#77)

| Benchmark | Llama 3.1-70B | MiMo-V2-Pro |
|---|---|---|
| LMArena Non-English | 1219 | 1416 |
| LMArena Chinese | 1215 | 1455 |
| LMArena French | 1260 | 1470 |
| LMArena German | 1222 | 1417 |
| LMArena Japanese | 1132 | 1366 |
| LMArena Korean | 1140 | 1401 |
| LMArena Russian | 1234 | 1427 |
| LMArena Spanish | 1253 | 1458 |

## Instruction Following

- Llama 3.1-70B: 65.5 (#218)
- MiMo-V2-Pro: 76.2 (#46)

| Benchmark | Llama 3.1-70B | MiMo-V2-Pro |
|---|---|---|
| LMArena Instruction Following | 1231 | 1444 |
| IFEval | 82.1% | — |

## Long Context

- Llama 3.1-70B: 37.6 (#208)
- MiMo-V2-Pro: 41.5 (#133)

| Benchmark | Llama 3.1-70B | MiMo-V2-Pro |
|---|---|---|
| LMArena Longer Query | 1241 | 1455 |
| CL-bench | — | 15.7% |
| CL-bench Life | — | 6.9% |

## Writing & Preference

- Llama 3.1-70B: 35.6 (#262)
- MiMo-V2-Pro: 62.9 (#67)

| Benchmark | Llama 3.1-70B | MiMo-V2-Pro |
|---|---|---|
| LMArena Text | 1261 | 1436 |
| LMArena Creative Writing | 1232 | 1415 |
| LMArena Multi-Turn | 1256 | 1456 |
| EQ-Bench Creative Writing | 784 | — |
| WildBench | 75.8% | — |

## FAQ

### Is Llama 3.1-70B better than MiMo-V2-Pro?

MiMo-V2-Pro is the stronger model overall, scoring 42.4 to 29.4 on the Noometry Index.

### Which is cheaper, Llama 3.1-70B or MiMo-V2-Pro?

Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; MiMo-V2-Pro lists at $0.43 and $0.87.

### Is Llama 3.1-70B or MiMo-V2-Pro better for coding?

MiMo-V2-Pro scores higher on coding benchmarks: 43.4 versus 29.8 in the Noometry coding category.

### Which has the bigger context window?

MiMo-V2-Pro does, with 1.05M tokens against 128K.

### How many benchmarks do Llama 3.1-70B and MiMo-V2-Pro share?

17 benchmarks have published results for both models. Llama 3.1-70B has 35 scored results on Noometry and MiMo-V2-Pro has 23.