Noometry

Model comparison

GLM-4.6V vs GLM-5.3

GLM-5.3 is the stronger model overall, scoring 54.8 to 41.3 on the Noometry Index. GLM-4.6V costs 4.8× less per token, which makes it the better buy when GLM-5.3's lead doesn't matter for your workload.

Last verified . 11 shared benchmarks.

GLM-4.6V Z.ai (Zhipu)

41.3

Rank #137 Confirmed

GLM-5.3 Z.ai (Zhipu)

54.8

Rank #26 Confirmed

Summary

  • They share 11 benchmarks with published results for both. GLM-4.6V scores higher in 0 categories and GLM-5.3 in 7 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-5.3 leads 58.3 to 38.0.
  • GLM-4.6V is cheaper at $0.30 / $0.90 per million input/output tokens, against $1.40 / $4.40 for GLM-5.3.
  • GLM-5.3 accepts more context: 1M tokens versus 128K.

Side by side

GLM-4.6VGLM-5.3
ProviderZ.ai (Zhipu)Z.ai (Zhipu)
Noometry Index41.354.8
Released2025-12-082026-08-14
WeightsOpenOpen
Context window128K1M
Max output33K131K
Input $ / M tokens$0.30$1.40
Output $ / M tokens$0.90$4.40
Results tracked1242

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Category by category

Coding GLM-5.3 leads

GLM-4.6V: 40.9 (#128), GLM-5.3: 59.5 (#14)

BenchmarkGLM-4.6VGLM-5.3
LMArena Coding13901496
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-4.6V: —, GLM-5.3: 36.4 (#38)

BenchmarkGLM-4.6VGLM-5.3
APEX-Agents—56.6%
Vending-Bench 2—8,164

Reasoning GLM-5.3 leads

GLM-4.6V: 27.6 (#115), GLM-5.3: 46.1 (#46)

BenchmarkGLM-4.6VGLM-5.3
LMArena Hard Prompts13681489
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 Not comparable

GLM-4.6V: —, GLM-5.3: 62.3 (#33)

BenchmarkGLM-4.6VGLM-5.3
FrontierMath (Tiers 1-3)—68.8%
FrontierMath Tier 4—29.3%
OTIS Mock AIME 2024-2025—91.1%
ProofBench—49%
LMArena Math—1489

Knowledge GLM-5.3 leads

GLM-4.6V: 38.0 (#149), GLM-5.3: 58.3 (#37)

BenchmarkGLM-4.6VGLM-5.3
LMArena Expert13711516
GPQA Diamond—90.9%
SimpleQA Verified—41%

Multimodal Not comparable

GLM-4.6V: 34.8 (#90), GLM-5.3: —

BenchmarkGLM-4.6VGLM-5.3
LMArena Vision1164—

Multilingual GLM-5.3 leads

GLM-4.6V: 48.6 (#141), GLM-5.3: 55.7 (#28)

BenchmarkGLM-4.6VGLM-5.3
LMArena Non-English13591457
LMArena Chinese14251528
LMArena Russian13401463
LMArena French—1499
LMArena German—1499
LMArena Japanese—1453
LMArena Korean—1472
LMArena Spanish—1460

Instruction Following GLM-5.3 leads

GLM-4.6V: 71.4 (#151), GLM-5.3: 77.5 (#23)

BenchmarkGLM-4.6VGLM-5.3
LMArena Instruction Following13521477

Long Context GLM-5.3 leads

GLM-4.6V: 41.3 (#143), GLM-5.3: 45.4 (#41)

BenchmarkGLM-4.6VGLM-5.3
LMArena Longer Query13581482

Writing & Preference GLM-5.3 leads

GLM-4.6V: 56.6 (#137), GLM-5.3: 75.7 (#6)

BenchmarkGLM-4.6VGLM-5.3
LMArena Text13771471
LMArena Creative Writing13471457
LMArena Multi-Turn13601472
EQ-Bench Creative Writing—2075

Frequently asked questions

Is GLM-4.6V better than GLM-5.3?

GLM-5.3 is the stronger model overall, scoring 54.8 to 41.3 on the Noometry Index. GLM-4.6V costs 4.8× 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-4.6V or GLM-5.3?

GLM-4.6V is cheaper. It lists at $0.30 per million input tokens and $0.90 per million output tokens; GLM-5.3 lists at $1.40 and $4.40.

Is GLM-4.6V or GLM-5.3 better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.5 versus 40.9 in the Noometry coding category.

Which has the bigger context window?

GLM-5.3 does, with 1M tokens against 128K.

How many benchmarks do GLM-4.6V and GLM-5.3 share?

11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and GLM-5.3 has 42.

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