Noometry

Model comparison

GLM-5.3-Flash vs MiniMax-M2.1

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 38.9 on the Noometry Index.

Last verified . 19 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

MiniMax-M2.1 MiniMax

38.9

Rank #178 Confirmed

Summary

  • They share 19 benchmarks with published results for both. GLM-5.3-Flash scores higher in 9 categories and MiniMax-M2.1 in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-5.3-Flash leads 48.0 to 16.6.
  • GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $0.30 / $1.20 for MiniMax-M2.1.
  • GLM-5.3-Flash accepts more context: 1M tokens versus 205K.

Side by side

GLM-5.3-FlashMiniMax-M2.1
ProviderZ.ai (Zhipu)MiniMax
Noometry Index51.838.9
Released2026-08-202025-12-23
WeightsOpenOpen
Context window1M205K
Max output131K131K
Input $ / M tokens$0.15$0.30
Output $ / M tokens$0.50$1.20
Results tracked4022

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

Category by category

Coding GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#31), MiniMax-M2.1: 40.4 (#143)

BenchmarkGLM-5.3-FlashMiniMax-M2.1
LMArena WebDev16091384
LMArena Coding15081421
ALE-Bench303.55623.83
DeepSWE63.4%—
FrontierCode31.8%—
CursorBench36.8%—
FrontierSWE18.1%—
SciCode51.6%—

Agentic & Tool Use GLM-5.3-Flash leads

GLM-5.3-Flash: 34.2 (#47), MiniMax-M2.1: 27.9 (#98)

BenchmarkGLM-5.3-FlashMiniMax-M2.1
Terminal-Bench—36.6%
APEX-Agents52.8%—
GDP.pdf14%—

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 48.0 (#42), MiniMax-M2.1: 16.6 (#302)

BenchmarkGLM-5.3-FlashMiniMax-M2.1
LMArena Hard Prompts14911411
ARC-AGI-265.8%—
NYT Connections (extended)—11.2%
ARC-AGI-191%—
CritPt15.4%—
Chess Puzzles14%—
Mystery Game Puzzles8%—
Surface Evolver Bench52.5%—
Bench to the Future 30.15—
Epoch Capabilities Index151.88—

Math GLM-5.3-Flash leads

GLM-5.3-Flash: 53.3 (#47), MiniMax-M2.1: 38.3 (#138)

BenchmarkGLM-5.3-FlashMiniMax-M2.1
LMArena Math15001397
FrontierMath (Tiers 1-3)55.8%—
FrontierMath Tier 417.1%—
OTIS Mock AIME 2024-202593.9%—
ProofBench21%—

Knowledge GLM-5.3-Flash leads

GLM-5.3-Flash: 58.4 (#36), MiniMax-M2.1: 38.3 (#147)

BenchmarkGLM-5.3-FlashMiniMax-M2.1
LMArena Expert15131431
GPQA Diamond90.2%—
Vectara Hallucination Rate—11.8%

Multimodal Not comparable

GLM-5.3-Flash: 42.8 (#27), MiniMax-M2.1: —

BenchmarkGLM-5.3-FlashMiniMax-M2.1
LMArena Vision1296—

Multilingual GLM-5.3-Flash leads

GLM-5.3-Flash: 56.0 (#25), MiniMax-M2.1: 50.0 (#128)

BenchmarkGLM-5.3-FlashMiniMax-M2.1
LMArena Non-English14621378
LMArena Chinese15271430
LMArena French14961404
LMArena German14701381
LMArena Japanese14291287
LMArena Korean14461298
LMArena Russian14691387
LMArena Spanish14711397

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.5 (#20), MiniMax-M2.1: 73.8 (#112)

BenchmarkGLM-5.3-FlashMiniMax-M2.1
LMArena Instruction Following14781400

Long Context GLM-5.3-Flash leads

GLM-5.3-Flash: 45.4 (#39), MiniMax-M2.1: 43.2 (#101)

BenchmarkGLM-5.3-FlashMiniMax-M2.1
LMArena Longer Query14821416

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.3 (#50), MiniMax-M2.1: 58.3 (#120)

BenchmarkGLM-5.3-FlashMiniMax-M2.1
LMArena Text14711392
LMArena Creative Writing14421361
LMArena Multi-Turn14671396

Frequently asked questions

Is GLM-5.3-Flash better than MiniMax-M2.1?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 38.9 on the Noometry Index.

Which is cheaper, GLM-5.3-Flash or MiniMax-M2.1?

GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; MiniMax-M2.1 lists at $0.30 and $1.20.

Is GLM-5.3-Flash or MiniMax-M2.1 better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 40.4 in the Noometry coding category.

Which has the bigger context window?

GLM-5.3-Flash does, with 1M tokens against 205K.

How many benchmarks do GLM-5.3-Flash and MiniMax-M2.1 share?

19 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and MiniMax-M2.1 has 22.

Related comparisons

Go deeper