# Llama 4 Maverick vs MiniMax-M2.7

> MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 30.9 on the Noometry Index. Llama 4 Maverick costs 1.7× less per token, which makes it the better buy when MiniMax-M2.7's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/llama-4-maverick-vs-minimax-m2-7
- Last updated: 2026-10-10
- Shared benchmarks: 24

## Summary

- They share 24 benchmarks with published results for both. Llama 4 Maverick scores higher in 2 categories and MiniMax-M2.7 in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiniMax-M2.7 leads 58.9 to 38.8.
- The biggest single-benchmark swing is NYT Connections (extended): 8% for Llama 4 Maverick and 24.7% for MiniMax-M2.7.
- Llama 4 Maverick is cheaper at $0.19 / $0.65 per million input/output tokens, against $0.30 / $1.20 for MiniMax-M2.7.
- MiniMax-M2.7 accepts more context: 205K tokens versus 128K.

## Snapshot

| | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| Provider | Meta | MiniMax |
| Noometry Index | 30.9 | 37.7 |
| Rank | 282 | 196 |
| Context | 128K | 205K |
| Input $/M | $0.19 | $0.30 |
| Output $/M | $0.65 | $1.20 |
| Weights | Open | Open |

## Coding

- Llama 4 Maverick: 26.6 (#324)
- MiniMax-M2.7: 41.8 (#120)

| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| SciCode | 33.1% | 47% |
| WeirdML | 24.5% | 37% |
| LMArena Coding | 1302 | 1454 |
| ALE-Bench | 172.97 | 599.25 |
| SWE-bench Verified (bash only) | 21% | — |
| Aider Polyglot | 15.6% | — |
| LMArena WebDev | — | 1398 |
| BigCodeBench Instruct | 49.7% | — |
| BigCodeBench Complete | 61.4% | — |

## Agentic & Tool Use

- Llama 4 Maverick: 28.2 (#91)
- MiniMax-M2.7: 25.1 (#111)

| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| Terminal-Bench | — | 45.1% |
| Berkeley Function Calling Leaderboard | 37.3% | — |
| ExploitBench | — | 13.3% |
| GBAEval | — | 0% |

## Reasoning

- Llama 4 Maverick: 10.1 (#342)
- MiniMax-M2.7: 19.7 (#253)

| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| NYT Connections (extended) | 8% | 24.7% |
| CritPt | 0% | 0.6% |
| LMArena Hard Prompts | 1281 | 1422 |
| Epoch Capabilities Index | 132.2 | 145.85 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 27.7% | — |
| Kagi LLM Benchmark | 55.9% | — |
| ARC-AGI-1 | 4.4% | — |
| EnigmaEval | 0.6% | — |
| Thematic Generalization | — | 39.3% |
| DTBench | 61.9% | — |
| LMCA | 15.9% | — |
| ForecastBench | 57.5 | — |

## Math

- Llama 4 Maverick: 26.0 (#262)
- MiniMax-M2.7: 25.9 (#263)

| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| LMArena Math | 1299 | 1420 |
| OTIS Mock AIME 2024-2025 | 20.6% | — |
| ProofBench | — | 3% |
| Omni-MATH | 42.2% | — |
| MATH Level 5 | 73% | — |
| FrontierMath (Feb 2025 set) | 0.7% | — |

## Knowledge

- Llama 4 Maverick: 33.4 (#204)
- MiniMax-M2.7: 37.7 (#152)

| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| Vectara Hallucination Rate | 8.2% | 12.9% |
| LMArena Expert | 1259 | 1444 |
| GPQA Diamond | 67% | — |
| Humanity's Last Exam | 5.7% | — |
| MMLU-Pro | 81% | — |
| Confabulations | 22.6% | — |
| GPQA (HELM) | 65% | — |

## Multimodal

- Llama 4 Maverick: 31.6 (#105)
- MiniMax-M2.7: —

| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| LMArena Vision | 1142 | — |
| GeoBench | 52% | — |
| SpatialViz-Bench | 31.8% | — |

## Multilingual

- Llama 4 Maverick: 42.2 (#195)
- MiniMax-M2.7: 50.3 (#123)

| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| LMArena Non-English | 1269 | 1382 |
| LMArena Chinese | 1277 | 1441 |
| LMArena French | 1259 | 1421 |
| LMArena German | 1291 | 1398 |
| LMArena Japanese | 1207 | 1262 |
| LMArena Korean | 1203 | 1313 |
| LMArena Russian | 1286 | 1383 |
| LMArena Spanish | 1293 | 1403 |

## Instruction Following

- Llama 4 Maverick: 71.7 (#146)
- MiniMax-M2.7: 74.1 (#103)

| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| LMArena Instruction Following | 1267 | 1405 |
| IFEval | 90.8% | — |

## Long Context

- Llama 4 Maverick: 31.4 (#279)
- MiniMax-M2.7: 43.3 (#99)

| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| LMArena Longer Query | 1280 | 1419 |
| Fiction.LiveBench | 46.2% | — |

## Writing & Preference

- Llama 4 Maverick: 38.8 (#252)
- MiniMax-M2.7: 58.9 (#112)

| Benchmark | Llama 4 Maverick | MiniMax-M2.7 |
|---|---|---|
| LMArena Text | 1287 | 1405 |
| LMArena Creative Writing | 1267 | 1354 |
| LMArena Multi-Turn | 1289 | 1412 |
| Short-Story Creative Writing | 62% | — |
| EQ-Bench Creative Writing | 860 | — |
| WildBench | 80% | — |

## FAQ

### Is Llama 4 Maverick better than MiniMax-M2.7?

MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 30.9 on the Noometry Index. Llama 4 Maverick costs 1.7× less per token, which makes it the better buy when MiniMax-M2.7's lead doesn't matter for your workload.

### Which is cheaper, Llama 4 Maverick or MiniMax-M2.7?

Llama 4 Maverick is cheaper. It lists at $0.19 per million input tokens and $0.65 per million output tokens; MiniMax-M2.7 lists at $0.30 and $1.20.

### Is Llama 4 Maverick or MiniMax-M2.7 better for coding?

MiniMax-M2.7 scores higher on coding benchmarks: 41.8 versus 26.6 in the Noometry coding category.

### Which has the bigger context window?

MiniMax-M2.7 does, with 205K tokens against 128K.

### How many benchmarks do Llama 4 Maverick and MiniMax-M2.7 share?

24 benchmarks have published results for both models. Llama 4 Maverick has 54 scored results on Noometry and MiniMax-M2.7 has 30.