Model comparison

GLM-4.5V vs MiniMax-M2

GLM-4.5V is the stronger model overall, scoring 39.8 to 37.4 on the Noometry Index. MiniMax-M2 costs 1.7× less per token, which makes it the better buy when GLM-4.5V's lead doesn't matter for your workload.

Last verified . 14 shared benchmarks.

GLM-4.5V Z.ai (Zhipu)

39.8

Rank #158 Confirmed

MiniMax-M2 MiniMax

37.4

Rank #204 Confirmed

Summary

  • They share 14 benchmarks with published results for both. GLM-4.5V scores higher in 4 categories and MiniMax-M2 in 4 categories; one gap is clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-4.5V leads 27.4 to 19.4.
  • MiniMax-M2 is cheaper at $0.30 / $1.20 per million input/output tokens, against $0.60 / $1.80 for GLM-4.5V.
  • MiniMax-M2 accepts more context: 205K tokens versus 64K.

Side by side

GLM-4.5V and MiniMax-M2 specifications
GLM-4.5VMiniMax-M2
ProviderZ.ai (Zhipu)MiniMax
Noometry Index39.837.4
Released2025-08-112025-10-27
WeightsOpenOpen
Context window64K205K
Max output16K131K
Input $ / M tokens$0.60$0.30
Output $ / M tokens$1.80$1.20
Results tracked1521

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Category by category

Coding Too close to call

GLM-4.5V: 39.5 (#155), MiniMax-M2: 39.3 (#159)

Coding benchmarks
BenchmarkGLM-4.5VMiniMax-M2
LMArena Coding13471370
SWE-bench Verified (bash only)—61%
LMArena WebDev—1297

Agentic & Tool Use Not comparable

GLM-4.5V: —, MiniMax-M2: 25.1 (#109)

Agentic & Tool Use benchmarks
BenchmarkGLM-4.5VMiniMax-M2
Terminal-Bench—30%
Vending-Bench 2—160.6

Reasoning GLM-4.5V leads

GLM-4.5V: 27.4 (#119), MiniMax-M2: 19.4 (#258)

Reasoning benchmarks
BenchmarkGLM-4.5VMiniMax-M2
Kagi LLM Benchmark59.8%57.8%
LMArena Hard Prompts13341357
NYT Connections (extended)—14.8%

Math Too close to call

GLM-4.5V: 37.4 (#159), MiniMax-M2: 37.3 (#160)

Math benchmarks
BenchmarkGLM-4.5VMiniMax-M2
LMArena Math13541352

Knowledge Too close to call

GLM-4.5V: 37.5 (#156), MiniMax-M2: 37.0 (#163)

Knowledge benchmarks
BenchmarkGLM-4.5VMiniMax-M2
LMArena Expert13531337

Multimodal Not comparable

GLM-4.5V: 34.3 (#92), MiniMax-M2: —

Multimodal benchmarks
BenchmarkGLM-4.5VMiniMax-M2
LMArena Vision1154—

Multilingual Too close to call

GLM-4.5V: 44.6 (#177), MiniMax-M2: 45.3 (#171)

Multilingual benchmarks
BenchmarkGLM-4.5VMiniMax-M2
LMArena Non-English13031313
LMArena Chinese13371366
LMArena Russian12981331
LMArena Spanish13361326
LMArena French—1335
LMArena German—1355

Instruction Following Too close to call

GLM-4.5V: 69.2 (#175), MiniMax-M2: 70.2 (#166)

Instruction Following benchmarks
BenchmarkGLM-4.5VMiniMax-M2
LMArena Instruction Following13111328

Long Context Too close to call

GLM-4.5V: 39.6 (#171), MiniMax-M2: 40.5 (#153)

Long Context benchmarks
BenchmarkGLM-4.5VMiniMax-M2
LMArena Longer Query13041331

Writing & Preference Too close to call

GLM-4.5V: 52.5 (#170), MiniMax-M2: 53.0 (#162)

Writing & Preference benchmarks
BenchmarkGLM-4.5VMiniMax-M2
LMArena Text13331340
LMArena Creative Writing12951286
LMArena Multi-Turn13321361

Frequently asked questions

Is GLM-4.5V better than MiniMax-M2?

GLM-4.5V is the stronger model overall, scoring 39.8 to 37.4 on the Noometry Index. MiniMax-M2 costs 1.7× less per token, which makes it the better buy when GLM-4.5V's lead doesn't matter for your workload.

Which is cheaper, GLM-4.5V or MiniMax-M2?

MiniMax-M2 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; GLM-4.5V lists at $0.60 and $1.80.

Is GLM-4.5V or MiniMax-M2 better for coding?

They score almost the same on coding (39.5 vs 39.3); test both on your own repository before choosing.

Which has the bigger context window?

MiniMax-M2 does, with 205K tokens against 64K.

How many benchmarks do GLM-4.5V and MiniMax-M2 share?

14 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and MiniMax-M2 has 21.

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