# Llama 3.1-8B vs MiMo-V2.5

> MiMo-V2.5 is the stronger model overall, scoring 43.0 to 22.8 on the Noometry Index. Llama 3.1-8B costs 3.0× less per token, which makes it the better buy when MiMo-V2.5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/llama-3-1-8b-vs-mimo-v2-5
- Last updated: 2026-10-10
- Shared benchmarks: 19

## Summary

- They share 19 benchmarks with published results for both. Llama 3.1-8B scores higher in 0 categories and MiMo-V2.5 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where MiMo-V2.5 leads 40.2 to 8.0.
- The biggest single-benchmark swing is SciCode: 13.2% for Llama 3.1-8B and 43.1% for MiMo-V2.5.
- Llama 3.1-8B is cheaper at $0.05 / $0.08 per million input/output tokens, against $0.14 / $0.28 for MiMo-V2.5.
- MiMo-V2.5 accepts more context: 1.05M tokens versus 128K.

## Snapshot

| | Llama 3.1-8B | MiMo-V2.5 |
|---|---|---|
| Provider | Meta | Xiaomi |
| Noometry Index | 22.8 | 43.0 |
| Rank | 347 | 89 |
| Context | 128K | 1.05M |
| Input $/M | $0.05 | $0.14 |
| Output $/M | $0.08 | $0.28 |
| Weights | Open | Open |

## Coding

- Llama 3.1-8B: 19.9 (#335)
- MiMo-V2.5: 43.6 (#75)

| Benchmark | Llama 3.1-8B | MiMo-V2.5 |
|---|---|---|
| SciCode | 13.2% | 43.1% |
| LMArena Coding | 1195 | 1469 |
| LMArena WebDev | — | 1438 |
| WeirdML | 1.7% | — |
| BigCodeBench Instruct | 32.8% | — |
| BigCodeBench Complete | 40.5% | — |
| ALE-Bench | — | 513.95 |
| HumanEval+ | 62.8% | — |
| MBPP+ | 55.6% | — |

## Agentic & Tool Use

- Llama 3.1-8B: 22.3 (#123)
- MiMo-V2.5: —

| Benchmark | Llama 3.1-8B | MiMo-V2.5 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 25.8% | — |
| BALROG | 15.1% | — |

## Reasoning

- Llama 3.1-8B: 14.5 (#316)
- MiMo-V2.5: 27.8 (#98)

| Benchmark | Llama 3.1-8B | MiMo-V2.5 |
|---|---|---|
| CritPt | 0% | 3.7% |
| LMArena Hard Prompts | 1175 | 1450 |
| Chess Puzzles | 0% | — |
| DTBench | 50.9% | — |
| LMCA | 5.4% | — |
| Epoch Capabilities Index | 116.48 | — |
| PIQA | 81.2% | — |

## Math

- Llama 3.1-8B: 9.5 (#311)
- MiMo-V2.5: 35.4 (#145)

| Benchmark | Llama 3.1-8B | MiMo-V2.5 |
|---|---|---|
| LMArena Math | 1179 | 1436 |
| OTIS Mock AIME 2024-2025 | 1.7% | — |
| ProofBench | — | 16% |
| Omni-MATH | 13.7% | — |
| MATH Level 5 | 22.9% | — |
| GSM8K | 82.4% | — |

## Knowledge

- Llama 3.1-8B: 8.0 (#302)
- MiMo-V2.5: 40.2 (#109)

| Benchmark | Llama 3.1-8B | MiMo-V2.5 |
|---|---|---|
| LMArena Expert | 1144 | 1459 |
| GPQA Diamond | 27% | — |
| MMLU-Pro | 40.6% | — |
| GPQA (HELM) | 24.7% | — |
| BoolQ | 82.8% | — |
| MMLU | 56.1% | — |

## Multimodal

- Llama 3.1-8B: —
- MiMo-V2.5: 39.0 (#53)

| Benchmark | Llama 3.1-8B | MiMo-V2.5 |
|---|---|---|
| LMArena Vision | — | 1245 |

## Multilingual

- Llama 3.1-8B: 34.2 (#244)
- MiMo-V2.5: 52.0 (#96)

| Benchmark | Llama 3.1-8B | MiMo-V2.5 |
|---|---|---|
| LMArena Non-English | 1148 | 1404 |
| LMArena Chinese | 1151 | 1467 |
| LMArena French | 1176 | 1447 |
| LMArena German | 1144 | 1421 |
| LMArena Japanese | 1061 | 1304 |
| LMArena Korean | 1053 | 1363 |
| LMArena Russian | 1158 | 1395 |
| LMArena Spanish | 1169 | 1412 |

## Instruction Following

- Llama 3.1-8B: 59.1 (#253)
- MiMo-V2.5: 75.7 (#55)

| Benchmark | Llama 3.1-8B | MiMo-V2.5 |
|---|---|---|
| LMArena Instruction Following | 1159 | 1433 |
| IFEval | 74.3% | — |

## Long Context

- Llama 3.1-8B: 35.8 (#233)
- MiMo-V2.5: 44.1 (#69)

| Benchmark | Llama 3.1-8B | MiMo-V2.5 |
|---|---|---|
| LMArena Longer Query | 1182 | 1444 |

## Writing & Preference

- Llama 3.1-8B: 29.9 (#285)
- MiMo-V2.5: 61.8 (#82)

| Benchmark | Llama 3.1-8B | MiMo-V2.5 |
|---|---|---|
| LMArena Text | 1187 | 1427 |
| LMArena Creative Writing | 1154 | 1392 |
| LMArena Multi-Turn | 1172 | 1445 |
| EQ-Bench Creative Writing | 713 | — |
| WildBench | 68.7% | — |

## FAQ

### Is Llama 3.1-8B better than MiMo-V2.5?

MiMo-V2.5 is the stronger model overall, scoring 43.0 to 22.8 on the Noometry Index. Llama 3.1-8B costs 3.0× less per token, which makes it the better buy when MiMo-V2.5's lead doesn't matter for your workload.

### Which is cheaper, Llama 3.1-8B or MiMo-V2.5?

Llama 3.1-8B is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; MiMo-V2.5 lists at $0.14 and $0.28.

### Is Llama 3.1-8B or MiMo-V2.5 better for coding?

MiMo-V2.5 scores higher on coding benchmarks: 43.6 versus 19.9 in the Noometry coding category.

### Which has the bigger context window?

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

### How many benchmarks do Llama 3.1-8B and MiMo-V2.5 share?

19 benchmarks have published results for both models. Llama 3.1-8B has 43 scored results on Noometry and MiMo-V2.5 has 23.