Noometry

Model comparison

GLM-4.7-Flash vs MiniMax-M2

GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 37.4 on the Noometry Index.

Last verified . 15 shared benchmarks.

GLM-4.7-Flash Z.ai (Zhipu)

38.8

Rank #180 Confirmed

MiniMax-M2 MiniMax

37.4

Rank #204 Confirmed

Summary

  • They share 15 benchmarks with published results for both. GLM-4.7-Flash scores higher in 4 categories and MiniMax-M2 in 4 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where MiniMax-M2 leads 53.0 to 47.4.
  • GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.30 / $1.20 for MiniMax-M2.
  • MiniMax-M2 accepts more context: 205K tokens versus 200K.

Side by side

GLM-4.7-FlashMiniMax-M2
ProviderZ.ai (Zhipu)MiniMax
Noometry Index38.837.4
Released2026-01-192025-10-27
WeightsOpenOpen
Context window200K205K
Max output131K131K
Input $ / M tokens$0.06$0.30
Output $ / M tokens$0.40$1.20
Results tracked2121

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Category by category

Coding GLM-4.7-Flash leads

GLM-4.7-Flash: 40.6 (#135), MiniMax-M2: 39.3 (#159)

BenchmarkGLM-4.7-FlashMiniMax-M2
LMArena Coding13831370
SWE-bench Verified (bash only)—61%
LMArena WebDev—1297

Agentic & Tool Use Not comparable

GLM-4.7-Flash: —, MiniMax-M2: 25.1 (#109)

BenchmarkGLM-4.7-FlashMiniMax-M2
Terminal-Bench—30%
Vending-Bench 2—160.6

Reasoning GLM-4.7-Flash leads

GLM-4.7-Flash: 20.9 (#229), MiniMax-M2: 19.4 (#258)

BenchmarkGLM-4.7-FlashMiniMax-M2
LMArena Hard Prompts13561357
Kagi LLM Benchmark—57.8%
NYT Connections (extended)—14.8%
Chess Puzzles0%—

Math MiniMax-M2 leads

GLM-4.7-Flash: 36.1 (#173), MiniMax-M2: 37.3 (#160)

BenchmarkGLM-4.7-FlashMiniMax-M2
LMArena Math13551352
OTIS Mock AIME 2024-202558.3%—

Knowledge MiniMax-M2 leads

GLM-4.7-Flash: 35.5 (#184), MiniMax-M2: 37.0 (#163)

BenchmarkGLM-4.7-FlashMiniMax-M2
LMArena Expert13571337
GPQA Diamond60.5%—
Vectara Hallucination Rate9.3%—

Multilingual GLM-4.7-Flash leads

GLM-4.7-Flash: 46.5 (#158), MiniMax-M2: 45.3 (#171)

BenchmarkGLM-4.7-FlashMiniMax-M2
LMArena Non-English13301313
LMArena Chinese14031366
LMArena French13321335
LMArena German13371355
LMArena Russian13321331
LMArena Spanish13501326
LMArena Korean1283—

Instruction Following Too close to call

GLM-4.7-Flash: 70.1 (#167), MiniMax-M2: 70.2 (#166)

BenchmarkGLM-4.7-FlashMiniMax-M2
LMArena Instruction Following13271328

Long Context Too close to call

GLM-4.7-Flash: 40.9 (#148), MiniMax-M2: 40.5 (#153)

BenchmarkGLM-4.7-FlashMiniMax-M2
LMArena Longer Query13451331

Writing & Preference MiniMax-M2 leads

GLM-4.7-Flash: 47.4 (#210), MiniMax-M2: 53.0 (#162)

BenchmarkGLM-4.7-FlashMiniMax-M2
LMArena Text13511340
LMArena Creative Writing12971286
LMArena Multi-Turn13421361
EQ-Bench Creative Writing1125—

Frequently asked questions

Is GLM-4.7-Flash better than MiniMax-M2?

GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 37.4 on the Noometry Index.

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

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; MiniMax-M2 lists at $0.30 and $1.20.

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

GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 39.3 in the Noometry coding category.

Which has the bigger context window?

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

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

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

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