# MiniMax-M2.7 vs Qwen2.5 7B Instruct

> MiniMax-M2.7 is the stronger model overall, scoring 37.4 to 28.6 on the Noometry Index. Qwen2.5 7B Instruct 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/minimax-m2-7-vs-qwen2-5-7b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 1

## Summary

- They share 1 benchmark with published results for both. MiniMax-M2.7 scores higher in 7 categories and Qwen2.5 7B Instruct in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where MiniMax-M2.7 leads 37.1 to 17.0.
- Qwen2.5 7B Instruct is cheaper at $0.17 / $0.70 per million input/output tokens, against $0.30 / $1.20 for MiniMax-M2.7.
- MiniMax-M2.7 accepts more context: 205K tokens versus 131K.

## Snapshot

| | MiniMax-M2.7 | Qwen2.5 7B Instruct |
|---|---|---|
| Provider | MiniMax | Alibaba (Qwen) |
| Noometry Index | 37.4 | 28.6 |
| Rank | 188 | 314 |
| Context | 205K | 131K |
| Input $/M | $0.30 | $0.17 |
| Output $/M | $1.20 | $0.70 |
| Weights | Open | Open |

## Coding

- MiniMax-M2.7: 41.4 (#115)
- Qwen2.5 7B Instruct: 35.9 (#204)

| Benchmark | MiniMax-M2.7 | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena WebDev | 1397 | — |
| SciCode | 47% | — |
| WeirdML | 37% | — |
| BigCodeBench Instruct | — | 37.6% |
| LMArena Coding | 1454 | — |
| BigCodeBench Complete | — | 46.1% |
| ALE-Bench | 599.25 | — |

## Agentic & Tool Use

- MiniMax-M2.7: 24.9 (#103)
- Qwen2.5 7B Instruct: 23.5 (#117)

| Benchmark | MiniMax-M2.7 | Qwen2.5 7B Instruct |
|---|---|---|
| Terminal-Bench | 45.1% | — |
| BALROG | — | 7.8% |
| ExploitBench | 13.3% | — |
| GBAEval | 0% | — |

## Reasoning

- MiniMax-M2.7: 19.0 (#248)
- Qwen2.5 7B Instruct: 14.3 (#317)

| Benchmark | MiniMax-M2.7 | Qwen2.5 7B Instruct |
|---|---|---|
| Epoch Capabilities Index | 145.84 | 118.44 |
| NYT Connections (extended) | 24.7% | — |
| CritPt | 0.6% | — |
| Chess Puzzles | — | 0% |
| Thematic Generalization | 39.3% | — |
| LMArena Hard Prompts | 1422 | — |
| DTBench | — | 47.7% |
| LMCA | — | 6.4% |

## Math

- MiniMax-M2.7: 24.9 (#254)
- Qwen2.5 7B Instruct: 11.8 (#300)

| Benchmark | MiniMax-M2.7 | Qwen2.5 7B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 2.5% |
| ProofBench | 3% | — |
| Omni-MATH | — | 29.4% |
| LMArena Math | 1420 | — |

## Knowledge

- MiniMax-M2.7: 37.1 (#151)
- Qwen2.5 7B Instruct: 17.0 (#281)

| Benchmark | MiniMax-M2.7 | Qwen2.5 7B Instruct |
|---|---|---|
| GPQA Diamond | — | 35.5% |
| MMLU-Pro | — | 53.9% |
| Vectara Hallucination Rate | 12.9% | — |
| GPQA (HELM) | — | 34.1% |
| LMArena Expert | 1443 | — |
| MMLU | — | 72.9% |

## Multilingual

- MiniMax-M2.7: 50.5 (#120)
- Qwen2.5 7B Instruct: —

| Benchmark | MiniMax-M2.7 | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Non-English | 1382 | — |
| LMArena Chinese | 1439 | — |
| LMArena French | 1422 | — |
| LMArena German | 1398 | — |
| LMArena Japanese | 1261 | — |
| LMArena Korean | 1313 | — |
| LMArena Russian | 1383 | — |
| LMArena Spanish | 1403 | — |

## Instruction Following

- MiniMax-M2.7: 74.2 (#101)
- Qwen2.5 7B Instruct: 63.4 (#226)

| Benchmark | MiniMax-M2.7 | Qwen2.5 7B Instruct |
|---|---|---|
| IFEval | — | 74.1% |
| LMArena Instruction Following | 1404 | — |

## Long Context

- MiniMax-M2.7: 43.3 (#94)
- Qwen2.5 7B Instruct: —

| Benchmark | MiniMax-M2.7 | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Longer Query | 1419 | — |

## Writing & Preference

- MiniMax-M2.7: 59.1 (#107)
- Qwen2.5 7B Instruct: 48.8 (#194)

| Benchmark | MiniMax-M2.7 | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Text | 1404 | — |
| LMArena Creative Writing | 1354 | — |
| WildBench | — | 73.1% |
| LMArena Multi-Turn | 1413 | — |

## FAQ

### Is MiniMax-M2.7 better than Qwen2.5 7B Instruct?

MiniMax-M2.7 is the stronger model overall, scoring 37.4 to 28.6 on the Noometry Index. Qwen2.5 7B Instruct 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, MiniMax-M2.7 or Qwen2.5 7B Instruct?

Qwen2.5 7B Instruct is cheaper. It lists at $0.17 per million input tokens and $0.70 per million output tokens; MiniMax-M2.7 lists at $0.30 and $1.20.

### Is MiniMax-M2.7 or Qwen2.5 7B Instruct better for coding?

MiniMax-M2.7 scores higher on coding benchmarks: 41.4 versus 35.9 in the Noometry coding category.

### Which has the bigger context window?

MiniMax-M2.7 does, with 205K tokens against 131K.

### How many benchmarks do MiniMax-M2.7 and Qwen2.5 7B Instruct share?

1 benchmark has published results for both models. MiniMax-M2.7 has 30 scored results on Noometry and Qwen2.5 7B Instruct has 15.