Noometry

Model comparison

GLM-4.7 vs MiniMax-M2

GLM-4.7 is the stronger model overall, scoring 42.0 to 37.4 on the Noometry Index. MiniMax-M2 costs 1.9× less per token, which makes it the better buy when GLM-4.7's lead doesn't matter for your workload.

Last verified . 18 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

42.0

Rank #124 Confirmed

MiniMax-M2 MiniMax

37.4

Rank #204 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GLM-4.7 scores higher in 9 categories and MiniMax-M2 in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.7 leads 47.0 to 37.0.
  • MiniMax-M2 is cheaper at $0.30 / $1.20 per million input/output tokens, against $0.60 / $2.20 for GLM-4.7.

Side by side

GLM-4.7MiniMax-M2
ProviderZ.ai (Zhipu)MiniMax
Noometry Index42.037.4
Released2025-12-222025-10-27
WeightsOpenOpen
Context window205K205K
Max output131K131K
Input $ / M tokens$0.60$0.30
Output $ / M tokens$2.20$1.20
Results tracked3621

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Category by category

Coding GLM-4.7 leads

GLM-4.7: 44.0 (#79), MiniMax-M2: 39.3 (#159)

BenchmarkGLM-4.7MiniMax-M2
LMArena WebDev14351297
LMArena Coding14541370
SWE-bench Verified (bash only)—61%
SciCode45.1%—
ALE-Bench399.48—

Agentic & Tool Use GLM-4.7 leads

GLM-4.7: 26.5 (#103), MiniMax-M2: 25.1 (#109)

BenchmarkGLM-4.7MiniMax-M2
Terminal-Bench33.4%30%
Vending-Bench 22,377160.6

Reasoning GLM-4.7 leads

GLM-4.7: 24.3 (#164), MiniMax-M2: 19.4 (#258)

BenchmarkGLM-4.7MiniMax-M2
LMArena Hard Prompts14431357
SimpleBench47.7%—
Kagi LLM Benchmark—57.8%
NYT Connections (extended)—14.8%
CritPt1.7%—
Chess Puzzles6%—
Epoch Capabilities Index143.51—

Math GLM-4.7 leads

GLM-4.7: 38.6 (#135), MiniMax-M2: 37.3 (#160)

BenchmarkGLM-4.7MiniMax-M2
LMArena Math14231352
OTIS Mock AIME 2024-202583.3%—
ProofBench6%—
FrontierMath (Feb 2025 set)2.4%—
FrontierMath Tier 4 (v1)0%—

Knowledge GLM-4.7 leads

GLM-4.7: 47.0 (#80), MiniMax-M2: 37.0 (#163)

BenchmarkGLM-4.7MiniMax-M2
LMArena Expert14241337
GPQA Diamond83.3%—
SimpleQA Verified32.2%—
Vectara Hallucination Rate11.7%—

Multilingual GLM-4.7 leads

GLM-4.7: 52.8 (#79), MiniMax-M2: 45.3 (#171)

BenchmarkGLM-4.7MiniMax-M2
LMArena Non-English14171313
LMArena Chinese14951366
LMArena French14321335
LMArena German14241355
LMArena Russian14231331
LMArena Spanish14341326
LMArena Japanese1439—
LMArena Korean1399—

Instruction Following GLM-4.7 leads

GLM-4.7: 74.4 (#95), MiniMax-M2: 70.2 (#166)

BenchmarkGLM-4.7MiniMax-M2
LMArena Instruction Following14111328

Long Context GLM-4.7 leads

GLM-4.7: 42.8 (#116), MiniMax-M2: 40.5 (#153)

BenchmarkGLM-4.7MiniMax-M2
LMArena Longer Query14321331
CL-bench15.9%—
CL-bench Life10.9%—

Writing & Preference GLM-4.7 leads

GLM-4.7: 60.9 (#93), MiniMax-M2: 53.0 (#162)

BenchmarkGLM-4.7MiniMax-M2
LMArena Text14351340
LMArena Creative Writing14011286
LMArena Multi-Turn14461361
EQ-Bench Creative Writing1413—

Frequently asked questions

Is GLM-4.7 better than MiniMax-M2?

GLM-4.7 is the stronger model overall, scoring 42.0 to 37.4 on the Noometry Index. MiniMax-M2 costs 1.9× less per token, which makes it the better buy when GLM-4.7's lead doesn't matter for your workload.

Which is cheaper, GLM-4.7 or MiniMax-M2?

MiniMax-M2 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; GLM-4.7 lists at $0.60 and $2.20.

Is GLM-4.7 or MiniMax-M2 better for coding?

GLM-4.7 scores higher on coding benchmarks: 44.0 versus 39.3 in the Noometry coding category.

Which has the bigger context window?

Both accept 205K tokens.

How many benchmarks do GLM-4.7 and MiniMax-M2 share?

18 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and MiniMax-M2 has 21.

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