Noometry

Model comparison

MiniMax-M2.1 vs Qwen3.8 27B

Qwen3.8 27B is the stronger model overall, scoring 46.0 to 38.9 on the Noometry Index.

Last verified . 19 shared benchmarks.

MiniMax-M2.1 MiniMax

38.9

Rank #178 Confirmed

Qwen3.8 27B Alibaba (Qwen)

46.0

Rank #68 Confirmed

Summary

  • They share 19 benchmarks with published results for both. MiniMax-M2.1 scores higher in 1 category and Qwen3.8 27B in 8 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Qwen3.8 27B leads 41.0 to 16.6.
  • The biggest single-benchmark swing is NYT Connections (extended): 11.2% for MiniMax-M2.1 and 54.5% for Qwen3.8 27B.
  • MiniMax-M2.1 is cheaper at $0.30 / $1.20 per million input/output tokens, against $0.04 / $2.30 for Qwen3.8 27B.
  • Qwen3.8 27B accepts more context: 262K tokens versus 205K.

Side by side

MiniMax-M2.1Qwen3.8 27B
ProviderMiniMaxAlibaba (Qwen)
Noometry Index38.946.0
Released2025-12-232026-08-14
WeightsOpenOpen
Context window205K262K
Max output131K33K
Input $ / M tokens$0.30$0.04
Output $ / M tokens$1.20$2.30
Results tracked2231

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Category by category

Coding Qwen3.8 27B leads

MiniMax-M2.1: 40.4 (#143), Qwen3.8 27B: 50.5 (#44)

BenchmarkMiniMax-M2.1Qwen3.8 27B
LMArena WebDev13841593
LMArena Coding14211482
SciCode—46.6%
ALE-Bench623.83—

Agentic & Tool Use Qwen3.8 27B leads

MiniMax-M2.1: 27.9 (#98), Qwen3.8 27B: 32.9 (#57)

BenchmarkMiniMax-M2.1Qwen3.8 27B
Terminal-Bench36.6%—
APEX-Agents—47.5%

Reasoning Qwen3.8 27B leads

MiniMax-M2.1: 16.6 (#302), Qwen3.8 27B: 41.0 (#54)

BenchmarkMiniMax-M2.1Qwen3.8 27B
NYT Connections (extended)11.2%54.5%
LMArena Hard Prompts14111460
ARC-AGI-2—42.4%
ARC-AGI-1—87.5%
CritPt—5.4%
DTBench—88%
LMCA—41.4%
Surface Evolver Bench—45%
Epoch Capabilities Index—149.38

Math MiniMax-M2.1 leads

MiniMax-M2.1: 38.3 (#138), Qwen3.8 27B: 37.1 (#161)

BenchmarkMiniMax-M2.1Qwen3.8 27B
LMArena Math13971456
ProofBench—16%

Knowledge Qwen3.8 27B leads

MiniMax-M2.1: 38.3 (#147), Qwen3.8 27B: 41.6 (#109)

BenchmarkMiniMax-M2.1Qwen3.8 27B
LMArena Expert14311482
Vectara Hallucination Rate11.8%—

Multimodal Not comparable

MiniMax-M2.1: —, Qwen3.8 27B: 41.3 (#37)

BenchmarkMiniMax-M2.1Qwen3.8 27B
LMArena Vision—1271

Multilingual Qwen3.8 27B leads

MiniMax-M2.1: 50.0 (#128), Qwen3.8 27B: 53.7 (#60)

BenchmarkMiniMax-M2.1Qwen3.8 27B
LMArena Non-English13781430
LMArena Chinese14301504
LMArena French14041465
LMArena German13811438
LMArena Japanese12871384
LMArena Korean12981393
LMArena Russian13871415
LMArena Spanish13971448

Instruction Following Qwen3.8 27B leads

MiniMax-M2.1: 73.8 (#112), Qwen3.8 27B: 75.8 (#53)

BenchmarkMiniMax-M2.1Qwen3.8 27B
LMArena Instruction Following14001439

Long Context Qwen3.8 27B leads

MiniMax-M2.1: 43.2 (#101), Qwen3.8 27B: 44.3 (#70)

BenchmarkMiniMax-M2.1Qwen3.8 27B
LMArena Longer Query14161450

Writing & Preference Qwen3.8 27B leads

MiniMax-M2.1: 58.3 (#120), Qwen3.8 27B: 65.8 (#43)

BenchmarkMiniMax-M2.1Qwen3.8 27B
LMArena Text13921441
LMArena Creative Writing13611384
LMArena Multi-Turn13961441
EQ-Bench Creative Writing—1671

Frequently asked questions

Is MiniMax-M2.1 better than Qwen3.8 27B?

Qwen3.8 27B is the stronger model overall, scoring 46.0 to 38.9 on the Noometry Index.

Which is cheaper, MiniMax-M2.1 or Qwen3.8 27B?

MiniMax-M2.1 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; Qwen3.8 27B lists at $0.04 and $2.30.

Is MiniMax-M2.1 or Qwen3.8 27B better for coding?

Qwen3.8 27B scores higher on coding benchmarks: 50.5 versus 40.4 in the Noometry coding category.

Which has the bigger context window?

Qwen3.8 27B does, with 262K tokens against 205K.

How many benchmarks do MiniMax-M2.1 and Qwen3.8 27B share?

19 benchmarks have published results for both models. MiniMax-M2.1 has 22 scored results on Noometry and Qwen3.8 27B has 31.

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