Model comparison

GLM-5.1 vs MiniMax-M2.1

GLM-5.1 is the stronger model overall, scoring 47.8 to 38.9 on the Noometry Index. MiniMax-M2.1 costs 4.1× less per token, which makes it the better buy when GLM-5.1's lead doesn't matter for your workload.

Last verified . 20 shared benchmarks.

GLM-5.1 Z.ai (Zhipu)

47.8

Rank #59 Confirmed

MiniMax-M2.1 MiniMax

38.9

Rank #178 Confirmed

Summary

  • They share 20 benchmarks with published results for both. GLM-5.1 scores higher in 8 categories and MiniMax-M2.1 in 1 category; 9 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-5.1 leads 39.1 to 16.6.
  • The biggest single-benchmark swing is NYT Connections (extended): 77.7% for GLM-5.1 and 11.2% for MiniMax-M2.1.
  • MiniMax-M2.1 is cheaper at $0.30 / $1.20 per million input/output tokens, against $1.40 / $4.40 for GLM-5.1.
  • MiniMax-M2.1 accepts more context: 205K tokens versus 200K.

Side by side

GLM-5.1 and MiniMax-M2.1 specifications
GLM-5.1MiniMax-M2.1
ProviderZ.ai (Zhipu)MiniMax
Noometry Index47.838.9
Released2026-04-072025-12-23
WeightsOpenOpen
Context window200K205K
Max output131K131K
Input $ / M tokens$1.40$0.30
Output $ / M tokens$4.40$1.20
Results tracked4122

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Category by category

Coding GLM-5.1 leads

GLM-5.1: 48.7 (#55), MiniMax-M2.1: 40.4 (#143)

Coding benchmarks
BenchmarkGLM-5.1MiniMax-M2.1
LMArena WebDev15081384
LMArena Coding14851421
ALE-Bench887.1623.83
SWE-bench Verified74.2%—
SciCode43.8%—
WeirdML57.1%—

Agentic & Tool Use MiniMax-M2.1 leads

GLM-5.1: 24.9 (#113), MiniMax-M2.1: 27.9 (#98)

Agentic & Tool Use benchmarks
BenchmarkGLM-5.1MiniMax-M2.1
Terminal-Bench—36.6%
APEX-Agents40.9%—
ExploitBench18.1%—
GBAEval0%—
Vending-Bench 25,634—

Reasoning GLM-5.1 leads

GLM-5.1: 39.1 (#60), MiniMax-M2.1: 16.6 (#302)

Reasoning benchmarks
BenchmarkGLM-5.1MiniMax-M2.1
NYT Connections (extended)77.7%11.2%
LMArena Hard Prompts14721411
SimpleBench55.1%—
CritPt4.6%—
Chess Puzzles19%—
Thematic Generalization69.8%—
Epoch Capabilities Index149.84—

Math GLM-5.1 leads

GLM-5.1: 49.7 (#60), MiniMax-M2.1: 38.3 (#138)

Knowledge GLM-5.1 leads

GLM-5.1: 54.9 (#50), MiniMax-M2.1: 38.3 (#147)

Knowledge benchmarks
BenchmarkGLM-5.1MiniMax-M2.1
LMArena Expert14761431
GPQA Diamond89.9%—
SimpleQA Verified34%—
Vectara Hallucination Rate—11.8%

Multilingual GLM-5.1 leads

GLM-5.1: 55.0 (#36), MiniMax-M2.1: 50.0 (#128)

Multilingual benchmarks
BenchmarkGLM-5.1MiniMax-M2.1
LMArena Non-English14471378
LMArena Chinese15151430
LMArena French14741404
LMArena German14651381
LMArena Japanese14341287
LMArena Korean14181298
LMArena Russian14541387
LMArena Spanish14691397

Instruction Following GLM-5.1 leads

GLM-5.1: 76.3 (#42), MiniMax-M2.1: 73.8 (#112)

Instruction Following benchmarks
BenchmarkGLM-5.1MiniMax-M2.1
LMArena Instruction Following14511400

Long Context GLM-5.1 leads

GLM-5.1: 44.9 (#53), MiniMax-M2.1: 43.2 (#101)

Long Context benchmarks
BenchmarkGLM-5.1MiniMax-M2.1
LMArena Longer Query14661416

Writing & Preference GLM-5.1 leads

GLM-5.1: 66.9 (#31), MiniMax-M2.1: 58.3 (#120)

Writing & Preference benchmarks
BenchmarkGLM-5.1MiniMax-M2.1
LMArena Text14611392
LMArena Creative Writing14531361
LMArena Multi-Turn14721396
EQ-Bench Creative Writing1592—

Frequently asked questions

Is GLM-5.1 better than MiniMax-M2.1?

GLM-5.1 is the stronger model overall, scoring 47.8 to 38.9 on the Noometry Index. MiniMax-M2.1 costs 4.1× less per token, which makes it the better buy when GLM-5.1's lead doesn't matter for your workload.

Which is cheaper, GLM-5.1 or MiniMax-M2.1?

MiniMax-M2.1 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; GLM-5.1 lists at $1.40 and $4.40.

Is GLM-5.1 or MiniMax-M2.1 better for coding?

GLM-5.1 scores higher on coding benchmarks: 48.7 versus 40.4 in the Noometry coding category.

Which has the bigger context window?

MiniMax-M2.1 does, with 205K tokens against 200K.

How many benchmarks do GLM-5.1 and MiniMax-M2.1 share?

20 benchmarks have published results for both models. GLM-5.1 has 41 scored results on Noometry and MiniMax-M2.1 has 22.

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