Noometry

Model comparison

MiniMax-M2.7 vs Qwen2.5-VL 72B Instruct

MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 29.9 on the Noometry Index.

Last verified . 0 shared benchmarks.

MiniMax-M2.7 MiniMax

37.7

Rank #196 Confirmed

Qwen2.5-VL 72B Instruct Alibaba (Qwen)

29.9

Rank #302 Confirmed

Summary

  • The widest gap is in agentic & tool use, where MiniMax-M2.7 leads 25.1 to 18.6.
  • MiniMax-M2.7 is cheaper at $0.30 / $1.20 per million input/output tokens, against $2.80 / $8.40 for Qwen2.5-VL 72B Instruct.
  • MiniMax-M2.7 accepts more context: 205K tokens versus 131K.

Side by side

MiniMax-M2.7Qwen2.5-VL 72B Instruct
ProviderMiniMaxAlibaba (Qwen)
Noometry Index37.729.9
Released2026-03-182024-09
WeightsOpenOpen
Context window205K131K
Max output131K8K
Input $ / M tokens$0.30$2.80
Output $ / M tokens$1.20$8.40
Results tracked306

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Category by category

Coding Not comparable

MiniMax-M2.7: 41.8 (#120), Qwen2.5-VL 72B Instruct: —

BenchmarkMiniMax-M2.7Qwen2.5-VL 72B Instruct
LMArena WebDev1398—
SciCode47%—
WeirdML37%—
LMArena Coding1454—
ALE-Bench599.25—

Agentic & Tool Use MiniMax-M2.7 leads

MiniMax-M2.7: 25.1 (#111), Qwen2.5-VL 72B Instruct: 18.6 (#144)

BenchmarkMiniMax-M2.7Qwen2.5-VL 72B Instruct
Terminal-Bench45.1%—
OSWorld—5%
ExploitBench13.3%—
GBAEval0%—

Reasoning Qwen2.5-VL 72B Instruct leads

MiniMax-M2.7: 19.7 (#253), Qwen2.5-VL 72B Instruct: 20.7 (#233)

BenchmarkMiniMax-M2.7Qwen2.5-VL 72B Instruct
Kagi LLM Benchmark—36%
NYT Connections (extended)24.7%—
CritPt0.6%—
Thematic Generalization39.3%—
LMArena Hard Prompts1422—
Epoch Capabilities Index145.85—

Math Not comparable

MiniMax-M2.7: 25.9 (#263), Qwen2.5-VL 72B Instruct: —

BenchmarkMiniMax-M2.7Qwen2.5-VL 72B Instruct
ProofBench3%—
LMArena Math1420—

Knowledge Not comparable

MiniMax-M2.7: 37.7 (#152), Qwen2.5-VL 72B Instruct: —

BenchmarkMiniMax-M2.7Qwen2.5-VL 72B Instruct
Vectara Hallucination Rate12.9%—
LMArena Expert1444—

Multimodal Not comparable

MiniMax-M2.7: —, Qwen2.5-VL 72B Instruct: 33.5 (#97)

BenchmarkMiniMax-M2.7Qwen2.5-VL 72B Instruct
LMArena Vision—1107
Video-MME—73.5%
GeoBench—62%
SpatialViz-Bench—33.3%

Multilingual Not comparable

MiniMax-M2.7: 50.3 (#123), Qwen2.5-VL 72B Instruct: —

BenchmarkMiniMax-M2.7Qwen2.5-VL 72B Instruct
LMArena Non-English1382—
LMArena Chinese1441—
LMArena French1421—
LMArena German1398—
LMArena Japanese1262—
LMArena Korean1313—
LMArena Russian1383—
LMArena Spanish1403—

Instruction Following Not comparable

MiniMax-M2.7: 74.1 (#103), Qwen2.5-VL 72B Instruct: —

BenchmarkMiniMax-M2.7Qwen2.5-VL 72B Instruct
LMArena Instruction Following1405—

Long Context Not comparable

MiniMax-M2.7: 43.3 (#99), Qwen2.5-VL 72B Instruct: —

BenchmarkMiniMax-M2.7Qwen2.5-VL 72B Instruct
LMArena Longer Query1419—

Writing & Preference Not comparable

MiniMax-M2.7: 58.9 (#112), Qwen2.5-VL 72B Instruct: —

BenchmarkMiniMax-M2.7Qwen2.5-VL 72B Instruct
LMArena Text1405—
LMArena Creative Writing1354—
LMArena Multi-Turn1412—

Frequently asked questions

Is MiniMax-M2.7 better than Qwen2.5-VL 72B Instruct?

MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 29.9 on the Noometry Index.

Which is cheaper, MiniMax-M2.7 or Qwen2.5-VL 72B Instruct?

MiniMax-M2.7 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; Qwen2.5-VL 72B Instruct lists at $2.80 and $8.40.

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-VL 72B Instruct share?

0 benchmarks have published results for both models. MiniMax-M2.7 has 30 scored results on Noometry and Qwen2.5-VL 72B Instruct has 6.

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