Model comparison

GLM-5.3 vs MiniMax-01

GLM-5.3 has enough public results to be ranked (#26); MiniMax-01 does not yet, so treat this comparison as directional.

Last verified . 0 shared benchmarks.

GLM-5.3 Z.ai (Zhipu)

54.8

Rank #26 Confirmed

MiniMax-01 MiniMax

33.4

Unranked Sparse

Summary

  • The widest gap is in knowledge, where GLM-5.3 leads 58.3 to 33.6.
  • MiniMax-01 is cheaper at $0.20 / $1.10 per million input/output tokens, against $1.40 / $4.40 for GLM-5.3.
  • MiniMax-01 accepts more context: 1M tokens versus 1M.

Side by side

GLM-5.3 and MiniMax-01 specifications
GLM-5.3MiniMax-01
ProviderZ.ai (Zhipu)MiniMax
Noometry Index54.833.4
Released2026-08-14—
WeightsOpenOpen
Context window1M1M
Max output131K900K
Input $ / M tokens$1.40$0.20
Output $ / M tokens$4.40$1.10
Results tracked422

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Category by category

Coding Not comparable

GLM-5.3: 59.5 (#14), MiniMax-01: —

Coding benchmarks
BenchmarkGLM-5.3MiniMax-01
DeepSWE69%—
FrontierCode40.1%—
CursorBench42.6%—
LMArena WebDev1622—
FrontierSWE30.2%—
SciCode59%—
WeirdML75.4%—
LMArena Coding1496—
ALE-Bench1,317—

Agentic & Tool Use Not comparable

GLM-5.3: 36.4 (#38), MiniMax-01: —

Agentic & Tool Use benchmarks
BenchmarkGLM-5.3MiniMax-01
APEX-Agents56.6%—
Vending-Bench 28,164—

Reasoning GLM-5.3 leads

GLM-5.3: 46.1 (#46), MiniMax-01: 22.4

Reasoning benchmarks
BenchmarkGLM-5.3MiniMax-01
Kagi LLM Benchmark—42.5%
NYT Connections (extended)74.2%—
CritPt19.1%—
Chess Puzzles21%—
LMArena Hard Prompts1489—
Mystery Game Puzzles33%—
DTBench87.7%—
LMCA55.5%—
Bench to the Future 30.15—
Epoch Capabilities Index155.61—

Math Not comparable

GLM-5.3: 62.3 (#33), MiniMax-01: —

Math benchmarks
BenchmarkGLM-5.3MiniMax-01
FrontierMath (Tiers 1-3)68.8%—
FrontierMath Tier 429.3%—
OTIS Mock AIME 2024-202591.1%—
ProofBench49%—
LMArena Math1489—

Knowledge GLM-5.3 leads

GLM-5.3: 58.3 (#37), MiniMax-01: 33.6

Knowledge benchmarks
BenchmarkGLM-5.3MiniMax-01
GPQA Diamond90.9%—
SimpleQA Verified41%—
Confabulations—23.9%
LMArena Expert1516—

Multilingual Not comparable

GLM-5.3: 55.7 (#28), MiniMax-01: —

Multilingual benchmarks
BenchmarkGLM-5.3MiniMax-01
LMArena Non-English1457—
LMArena Chinese1528—
LMArena French1499—
LMArena German1499—
LMArena Japanese1453—
LMArena Korean1472—
LMArena Russian1463—
LMArena Spanish1460—

Instruction Following Not comparable

GLM-5.3: 77.5 (#23), MiniMax-01: —

Instruction Following benchmarks
BenchmarkGLM-5.3MiniMax-01
LMArena Instruction Following1477—

Long Context Not comparable

GLM-5.3: 45.4 (#41), MiniMax-01: —

Long Context benchmarks
BenchmarkGLM-5.3MiniMax-01
LMArena Longer Query1482—

Writing & Preference Not comparable

GLM-5.3: 75.7 (#6), MiniMax-01: —

Writing & Preference benchmarks
BenchmarkGLM-5.3MiniMax-01
LMArena Text1471—
LMArena Creative Writing1457—
EQ-Bench Creative Writing2075—
LMArena Multi-Turn1472—

Frequently asked questions

Is GLM-5.3 better than MiniMax-01?

GLM-5.3 has enough public results to be ranked (#26); MiniMax-01 does not yet, so treat this comparison as directional.

Which is cheaper, GLM-5.3 or MiniMax-01?

MiniMax-01 is cheaper. It lists at $0.20 per million input tokens and $1.10 per million output tokens; GLM-5.3 lists at $1.40 and $4.40.

Which has the bigger context window?

MiniMax-01 does, with 1M tokens against 1M.

How many benchmarks do GLM-5.3 and MiniMax-01 share?

0 benchmarks have published results for both models. GLM-5.3 has 42 scored results on Noometry and MiniMax-01 has 2.

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