# Llama 4 Maverick vs MiMo-V2-Pro

> MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 30.9 on the Noometry Index. Llama 4 Maverick costs 1.8× less per token, which makes it the better buy when MiMo-V2-Pro's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/llama-4-maverick-vs-mimo-v2-pro
- Last updated: 2026-10-10
- Shared benchmarks: 19

## Summary

- They share 19 benchmarks with published results for both. Llama 4 Maverick scores higher in 0 categories and MiMo-V2-Pro in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiMo-V2-Pro leads 62.8 to 38.8.
- The biggest single-benchmark swing is NYT Connections (extended): 8% for Llama 4 Maverick and 25.8% for MiMo-V2-Pro.
- Llama 4 Maverick is cheaper at $0.19 / $0.65 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 4 Maverick has downloadable open weights; the other is API-only.

## Snapshot

| | Llama 4 Maverick | MiMo-V2-Pro |
|---|---|---|
| Provider | Meta | Xiaomi |
| Noometry Index | 30.9 | 43.0 |
| Rank | 282 | 103 |
| Context | 128K | 1.05M |
| Input $/M | $0.19 | $0.43 |
| Output $/M | $0.65 | $0.87 |
| Weights | Open | Proprietary |

## Coding

- Llama 4 Maverick: 26.6 (#324)
- MiMo-V2-Pro: 43.8 (#83)

| Benchmark | Llama 4 Maverick | MiMo-V2-Pro |
|---|---|---|
| LMArena Coding | 1302 | 1476 |
| ALE-Bench | 172.97 | 785.17 |
| SWE-bench Verified (bash only) | 21% | — |
| Aider Polyglot | 15.6% | — |
| LMArena WebDev | — | 1433 |
| SciCode | 33.1% | — |
| WeirdML | 24.5% | — |
| BigCodeBench Instruct | 49.7% | — |
| BigCodeBench Complete | 61.4% | — |

## Agentic & Tool Use

- Llama 4 Maverick: 28.2 (#91)
- MiMo-V2-Pro: —

| Benchmark | Llama 4 Maverick | MiMo-V2-Pro |
|---|---|---|
| Berkeley Function Calling Leaderboard | 37.3% | — |

## Reasoning

- Llama 4 Maverick: 10.1 (#342)
- MiMo-V2-Pro: 22.1 (#206)

| Benchmark | Llama 4 Maverick | MiMo-V2-Pro |
|---|---|---|
| NYT Connections (extended) | 8% | 25.8% |
| LMArena Hard Prompts | 1281 | 1457 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 27.7% | — |
| Kagi LLM Benchmark | 55.9% | — |
| ARC-AGI-1 | 4.4% | — |
| CritPt | 0% | — |
| EnigmaEval | 0.6% | — |
| Thematic Generalization | — | 45.9% |
| DTBench | 61.9% | — |
| LMCA | 15.9% | — |
| Epoch Capabilities Index | 132.2 | — |
| ForecastBench | 57.5 | — |

## Math

- Llama 4 Maverick: 26.0 (#262)
- MiMo-V2-Pro: 39.5 (#102)

| Benchmark | Llama 4 Maverick | MiMo-V2-Pro |
|---|---|---|
| LMArena Math | 1299 | 1447 |
| OTIS Mock AIME 2024-2025 | 20.6% | — |
| Omni-MATH | 42.2% | — |
| MATH Level 5 | 73% | — |
| FrontierMath (Feb 2025 set) | 0.7% | — |

## Knowledge

- Llama 4 Maverick: 33.4 (#204)
- MiMo-V2-Pro: 41.4 (#111)

| Benchmark | Llama 4 Maverick | MiMo-V2-Pro |
|---|---|---|
| LMArena Expert | 1259 | 1478 |
| GPQA Diamond | 67% | — |
| Humanity's Last Exam | 5.7% | — |
| MMLU-Pro | 81% | — |
| Confabulations | 22.6% | — |
| Vectara Hallucination Rate | 8.2% | — |
| GPQA (HELM) | 65% | — |

## Multimodal

- Llama 4 Maverick: 31.6 (#105)
- MiMo-V2-Pro: —

| Benchmark | Llama 4 Maverick | MiMo-V2-Pro |
|---|---|---|
| LMArena Vision | 1142 | — |
| GeoBench | 52% | — |
| SpatialViz-Bench | 31.8% | — |

## Multilingual

- Llama 4 Maverick: 42.2 (#195)
- MiMo-V2-Pro: 52.7 (#81)

| Benchmark | Llama 4 Maverick | MiMo-V2-Pro |
|---|---|---|
| LMArena Non-English | 1269 | 1416 |
| LMArena Chinese | 1277 | 1456 |
| LMArena French | 1259 | 1469 |
| LMArena German | 1291 | 1417 |
| LMArena Japanese | 1207 | 1366 |
| LMArena Korean | 1203 | 1400 |
| LMArena Russian | 1286 | 1427 |
| LMArena Spanish | 1293 | 1457 |

## Instruction Following

- Llama 4 Maverick: 71.7 (#146)
- MiMo-V2-Pro: 76.0 (#49)

| Benchmark | Llama 4 Maverick | MiMo-V2-Pro |
|---|---|---|
| LMArena Instruction Following | 1267 | 1445 |
| IFEval | 90.8% | — |

## Long Context

- Llama 4 Maverick: 31.4 (#279)
- MiMo-V2-Pro: 41.5 (#138)

| Benchmark | Llama 4 Maverick | MiMo-V2-Pro |
|---|---|---|
| LMArena Longer Query | 1280 | 1455 |
| Fiction.LiveBench | 46.2% | — |
| CL-bench | — | 15.7% |
| CL-bench Life | — | 6.9% |

## Writing & Preference

- Llama 4 Maverick: 38.8 (#252)
- MiMo-V2-Pro: 62.8 (#70)

| Benchmark | Llama 4 Maverick | MiMo-V2-Pro |
|---|---|---|
| LMArena Text | 1287 | 1436 |
| LMArena Creative Writing | 1267 | 1415 |
| LMArena Multi-Turn | 1289 | 1456 |
| Short-Story Creative Writing | 62% | — |
| EQ-Bench Creative Writing | 860 | — |
| WildBench | 80% | — |

## FAQ

### Is Llama 4 Maverick better than MiMo-V2-Pro?

MiMo-V2-Pro is the stronger model overall, scoring 43.0 to 30.9 on the Noometry Index. Llama 4 Maverick costs 1.8× less per token, which makes it the better buy when MiMo-V2-Pro's lead doesn't matter for your workload.

### Which is cheaper, Llama 4 Maverick or MiMo-V2-Pro?

Llama 4 Maverick is cheaper. It lists at $0.19 per million input tokens and $0.65 per million output tokens; MiMo-V2-Pro lists at $0.43 and $0.87.

### Is Llama 4 Maverick or MiMo-V2-Pro better for coding?

MiMo-V2-Pro scores higher on coding benchmarks: 43.8 versus 26.6 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 4 Maverick and MiMo-V2-Pro share?

19 benchmarks have published results for both models. Llama 4 Maverick has 54 scored results on Noometry and MiMo-V2-Pro has 23.