# Llama 3.1-70B vs MiMo-V2.5-Pro

> MiMo-V2.5-Pro is the stronger model overall, scoring 44.8 to 29.4 on the Noometry Index.

- Canonical page: https://noometry.com/compare/llama-3-1-70b-vs-mimo-v2-5-pro
- Last updated: 2026-10-10
- Shared benchmarks: 20

## Summary

- They share 20 benchmarks with published results for both. Llama 3.1-70B scores higher in 0 categories and MiMo-V2.5-Pro in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiMo-V2.5-Pro leads 65.5 to 35.6.
- The biggest single-benchmark swing is DTBench: 60% for Llama 3.1-70B and 84.5% for MiMo-V2.5-Pro.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $0.43 / $0.87 for MiMo-V2.5-Pro.
- MiMo-V2.5-Pro accepts more context: 1.05M tokens versus 128K.

## Snapshot

| | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| Provider | Meta | Xiaomi |
| Noometry Index | 29.4 | 44.8 |
| Rank | 299 | 70 |
| Context | 128K | 1.05M |
| Input $/M | $0.40 | $0.43 |
| Output $/M | $0.40 | $0.87 |
| Weights | Open | Open |

## Coding

- Llama 3.1-70B: 29.8 (#292)
- MiMo-V2.5-Pro: 47.0 (#58)

| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Coding | 1260 | 1502 |
| LMArena WebDev | — | 1477 |
| SciCode | — | 50.2% |
| WeirdML | 9% | — |
| BigCodeBench Instruct | 46.1% | — |
| BigCodeBench Complete | 54.8% | — |
| ALE-Bench | — | 899.8 |

## Agentic & Tool Use

- Llama 3.1-70B: 24.9 (#104)
- MiMo-V2.5-Pro: —

| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| TheAgentCompany | 6.9% | — |
| BALROG | 27.9% | — |

## Reasoning

- Llama 3.1-70B: 20.8 (#215)
- MiMo-V2.5-Pro: 25.9 (#124)

| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Hard Prompts | 1241 | 1487 |
| DTBench | 60% | 84.5% |
| LMCA | 14.8% | 29.5% |
| NYT Connections (extended) | — | 34.4% |
| CritPt | — | 4% |
| Epoch Capabilities Index | 125.91 | — |

## Math

- Llama 3.1-70B: 12.7 (#298)
- MiMo-V2.5-Pro: 38.6 (#84)

| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Math | 1252 | 1480 |
| OTIS Mock AIME 2024-2025 | 3.6% | — |
| ProofBench | — | 22% |
| Omni-MATH | 21% | — |
| MATH Level 5 | 36.7% | — |

## Knowledge

- Llama 3.1-70B: 24.1 (#264)
- MiMo-V2.5-Pro: 41.5 (#100)

| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Expert | 1209 | 1501 |
| GPQA Diamond | 44.2% | — |
| MMLU-Pro | 65.3% | — |
| GPQA (HELM) | 42.6% | — |
| MMLU | 80.1% | — |

## Multilingual

- Llama 3.1-70B: 38.9 (#220)
- MiMo-V2.5-Pro: 55.3 (#33)

| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Non-English | 1219 | 1449 |
| LMArena Chinese | 1215 | 1507 |
| LMArena French | 1260 | 1489 |
| LMArena German | 1222 | 1455 |
| LMArena Japanese | 1132 | 1418 |
| LMArena Korean | 1140 | 1436 |
| LMArena Russian | 1234 | 1450 |
| LMArena Spanish | 1253 | 1470 |

## Instruction Following

- Llama 3.1-70B: 65.5 (#218)
- MiMo-V2.5-Pro: 77.6 (#21)

| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Instruction Following | 1231 | 1477 |
| IFEval | 82.1% | — |

## Long Context

- Llama 3.1-70B: 37.6 (#208)
- MiMo-V2.5-Pro: 45.4 (#38)

| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Longer Query | 1241 | 1482 |

## Writing & Preference

- Llama 3.1-70B: 35.6 (#262)
- MiMo-V2.5-Pro: 65.5 (#47)

| Benchmark | Llama 3.1-70B | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Text | 1261 | 1465 |
| LMArena Creative Writing | 1232 | 1440 |
| EQ-Bench Creative Writing | 784 | 1493 |
| LMArena Multi-Turn | 1256 | 1477 |
| WildBench | 75.8% | — |
| EQ-Bench 4 | — | 1208 |

## FAQ

### Is Llama 3.1-70B better than MiMo-V2.5-Pro?

MiMo-V2.5-Pro is the stronger model overall, scoring 44.8 to 29.4 on the Noometry Index.

### Which is cheaper, Llama 3.1-70B or MiMo-V2.5-Pro?

Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; MiMo-V2.5-Pro lists at $0.43 and $0.87.

### Is Llama 3.1-70B or MiMo-V2.5-Pro better for coding?

MiMo-V2.5-Pro scores higher on coding benchmarks: 47.0 versus 29.8 in the Noometry coding category.

### Which has the bigger context window?

MiMo-V2.5-Pro does, with 1.05M tokens against 128K.

### How many benchmarks do Llama 3.1-70B and MiMo-V2.5-Pro share?

20 benchmarks have published results for both models. Llama 3.1-70B has 35 scored results on Noometry and MiMo-V2.5-Pro has 27.