Noometry

Model comparison

GLM-4.6 vs MiniMax-M2

GLM-4.6 is the stronger model overall, scoring 40.9 to 36.9 on the Noometry Index. MiniMax-M2 costs 1.9× less per token, which makes it the better buy when GLM-4.6's lead doesn't matter for your workload.

Last verified . 19 shared benchmarks.

GLM-4.6 Z.ai (Zhipu)

40.9

Rank #132 Confirmed

MiniMax-M2 MiniMax

36.9

Rank #201 Confirmed

Summary

  • They share 19 benchmarks with published results for both. GLM-4.6 scores higher in 9 categories and MiniMax-M2 in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in multilingual, where GLM-4.6 leads 53.6 to 45.6.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 47.4% for GLM-4.6 and 57.8% for MiniMax-M2.
  • MiniMax-M2 is cheaper at $0.30 / $1.20 per million input/output tokens, against $0.60 / $2.20 for GLM-4.6.

Side by side

GLM-4.6MiniMax-M2
ProviderZ.ai (Zhipu)MiniMax
Noometry Index40.936.9
Released2025-09-302025-10-27
WeightsOpenOpen
Context window205K205K
Max output131K131K
Input $ / M tokens$0.60$0.30
Output $ / M tokens$2.20$1.20
Results tracked2921

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding Too close to call

GLM-4.6: 39.9 (#137), MiniMax-M2: 39.1 (#151)

BenchmarkGLM-4.6MiniMax-M2
SWE-bench Verified (bash only)55.4%61%
LMArena WebDev13391297
LMArena Coding14491370
SciCode38.4%—
ALE-Bench340.82—

Agentic & Tool Use GLM-4.6 leads

GLM-4.6: 32.1 (#60), MiniMax-M2: 24.9 (#102)

BenchmarkGLM-4.6MiniMax-M2
Terminal-Bench24.5%30%
Berkeley Function Calling Leaderboard72.4%—
Vending-Bench 2—160.6

Reasoning GLM-4.6 leads

GLM-4.6: 23.1 (#168), MiniMax-M2: 18.6 (#256)

BenchmarkGLM-4.6MiniMax-M2
Kagi LLM Benchmark47.4%57.8%
LMArena Hard Prompts14401357
NYT Connections (extended)—14.8%
CritPt1.1%—

Math GLM-4.6 leads

GLM-4.6: 36.4 (#115), MiniMax-M2: 34.6 (#158)

BenchmarkGLM-4.6MiniMax-M2
LMArena Math14311350
FrontierMath (Feb 2025 set)3.8%—
FrontierMath Tier 4 (v1)2.1%—

Knowledge GLM-4.6 leads

GLM-4.6: 39.6 (#118), MiniMax-M2: 36.3 (#160)

BenchmarkGLM-4.6MiniMax-M2
LMArena Expert14321336
Vectara Hallucination Rate9.5%—

Multilingual GLM-4.6 leads

GLM-4.6: 53.6 (#62), MiniMax-M2: 45.6 (#165)

BenchmarkGLM-4.6MiniMax-M2
LMArena Non-English14261314
LMArena Chinese15001367
LMArena French14591336
LMArena German14471366
LMArena Russian14181332
LMArena Spanish14361326
LMArena Japanese1394—
LMArena Korean1401—

Instruction Following GLM-4.6 leads

GLM-4.6: 74.5 (#93), MiniMax-M2: 70.4 (#160)

BenchmarkGLM-4.6MiniMax-M2
LMArena Instruction Following14101329

Long Context GLM-4.6 leads

GLM-4.6: 43.4 (#91), MiniMax-M2: 40.5 (#148)

BenchmarkGLM-4.6MiniMax-M2
LMArena Longer Query14231332

Writing & Preference GLM-4.6 leads

GLM-4.6: 61.3 (#86), MiniMax-M2: 53.3 (#157)

BenchmarkGLM-4.6MiniMax-M2
LMArena Text14401340
LMArena Creative Writing14111288
LMArena Multi-Turn14271362
EQ-Bench Creative Writing1411—

Frequently asked questions

Is GLM-4.6 better than MiniMax-M2?

GLM-4.6 is the stronger model overall, scoring 40.9 to 36.9 on the Noometry Index. MiniMax-M2 costs 1.9× less per token, which makes it the better buy when GLM-4.6's lead doesn't matter for your workload.

Which is cheaper, GLM-4.6 or MiniMax-M2?

MiniMax-M2 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; GLM-4.6 lists at $0.60 and $2.20.

Is GLM-4.6 or MiniMax-M2 better for coding?

They score almost the same on coding (39.9 vs 39.1); test both on your own repository before choosing.

Which has the bigger context window?

Both accept 205K tokens.

How many benchmarks do GLM-4.6 and MiniMax-M2 share?

19 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and MiniMax-M2 has 21.

Related comparisons

Go deeper