Noometry

Model comparison

GLM-4.5V vs GLM-5.3

GLM-5.3 is the stronger model overall, scoring 54.8 to 39.8 on the Noometry Index. GLM-4.5V costs 2.4× less per token, which makes it the better buy when GLM-5.3's lead doesn't matter for your workload.

Last verified . 13 shared benchmarks.

GLM-4.5V Z.ai (Zhipu)

39.8

Rank #158 Confirmed

GLM-5.3 Z.ai (Zhipu)

54.8

Rank #26 Confirmed

Summary

  • They share 13 benchmarks with published results for both. GLM-4.5V scores higher in 0 categories and GLM-5.3 in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-5.3 leads 62.3 to 37.4.
  • GLM-4.5V is cheaper at $0.60 / $1.80 per million input/output tokens, against $1.40 / $4.40 for GLM-5.3.
  • GLM-5.3 accepts more context: 1M tokens versus 64K.

Side by side

GLM-4.5VGLM-5.3
ProviderZ.ai (Zhipu)Z.ai (Zhipu)
Noometry Index39.854.8
Released2025-08-112026-08-14
WeightsOpenOpen
Context window64K1M
Max output16K131K
Input $ / M tokens$0.60$1.40
Output $ / M tokens$1.80$4.40
Results tracked1542

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Category by category

Coding GLM-5.3 leads

GLM-4.5V: 39.5 (#155), GLM-5.3: 59.5 (#14)

BenchmarkGLM-4.5VGLM-5.3
LMArena Coding13471496
DeepSWE—69%
FrontierCode—40.1%
CursorBench—42.6%
LMArena WebDev—1622
FrontierSWE—30.2%
SciCode—59%
WeirdML—75.4%
ALE-Bench—1,317

Agentic & Tool Use Not comparable

GLM-4.5V: —, GLM-5.3: 36.4 (#38)

BenchmarkGLM-4.5VGLM-5.3
APEX-Agents—56.6%
Vending-Bench 2—8,164

Reasoning GLM-5.3 leads

GLM-4.5V: 27.4 (#119), GLM-5.3: 46.1 (#46)

BenchmarkGLM-4.5VGLM-5.3
LMArena Hard Prompts13341489
Kagi LLM Benchmark59.8%—
NYT Connections (extended)—74.2%
CritPt—19.1%
Chess Puzzles—21%
Mystery Game Puzzles—33%
DTBench—87.7%
LMCA—55.5%
Bench to the Future 3—0.15
Epoch Capabilities Index—155.61

Math GLM-5.3 leads

GLM-4.5V: 37.4 (#159), GLM-5.3: 62.3 (#33)

BenchmarkGLM-4.5VGLM-5.3
LMArena Math13541489
FrontierMath (Tiers 1-3)—68.8%
FrontierMath Tier 4—29.3%
OTIS Mock AIME 2024-2025—91.1%
ProofBench—49%

Knowledge GLM-5.3 leads

GLM-4.5V: 37.5 (#156), GLM-5.3: 58.3 (#37)

BenchmarkGLM-4.5VGLM-5.3
LMArena Expert13531516
GPQA Diamond—90.9%
SimpleQA Verified—41%

Multimodal Not comparable

GLM-4.5V: 34.3 (#92), GLM-5.3: —

BenchmarkGLM-4.5VGLM-5.3
LMArena Vision1154—

Multilingual GLM-5.3 leads

GLM-4.5V: 44.6 (#177), GLM-5.3: 55.7 (#28)

BenchmarkGLM-4.5VGLM-5.3
LMArena Non-English13031457
LMArena Chinese13371528
LMArena Russian12981463
LMArena Spanish13361460
LMArena French—1499
LMArena German—1499
LMArena Japanese—1453
LMArena Korean—1472

Instruction Following GLM-5.3 leads

GLM-4.5V: 69.2 (#175), GLM-5.3: 77.5 (#23)

BenchmarkGLM-4.5VGLM-5.3
LMArena Instruction Following13111477

Long Context GLM-5.3 leads

GLM-4.5V: 39.6 (#171), GLM-5.3: 45.4 (#41)

BenchmarkGLM-4.5VGLM-5.3
LMArena Longer Query13041482

Writing & Preference GLM-5.3 leads

GLM-4.5V: 52.5 (#170), GLM-5.3: 75.7 (#6)

BenchmarkGLM-4.5VGLM-5.3
LMArena Text13331471
LMArena Creative Writing12951457
LMArena Multi-Turn13321472
EQ-Bench Creative Writing—2075

Frequently asked questions

Is GLM-4.5V better than GLM-5.3?

GLM-5.3 is the stronger model overall, scoring 54.8 to 39.8 on the Noometry Index. GLM-4.5V costs 2.4× less per token, which makes it the better buy when GLM-5.3's lead doesn't matter for your workload.

Which is cheaper, GLM-4.5V or GLM-5.3?

GLM-4.5V is cheaper. It lists at $0.60 per million input tokens and $1.80 per million output tokens; GLM-5.3 lists at $1.40 and $4.40.

Is GLM-4.5V or GLM-5.3 better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.5 versus 39.5 in the Noometry coding category.

Which has the bigger context window?

GLM-5.3 does, with 1M tokens against 64K.

How many benchmarks do GLM-4.5V and GLM-5.3 share?

13 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and GLM-5.3 has 42.

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