Noometry

Model comparison

GLM-4.5V vs GPT-4 Turbo

GLM-4.5V is the stronger model overall, scoring 39.8 to 30.5 on the Noometry Index.

Last verified . 14 shared benchmarks.

GLM-4.5V Z.ai (Zhipu)

39.8

Rank #158 Confirmed

GPT-4 Turbo OpenAI

30.5

Rank #292 Confirmed

Summary

  • They share 14 benchmarks with published results for both. GLM-4.5V scores higher in 9 categories and GPT-4 Turbo in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-4.5V leads 37.4 to 9.0.
  • GLM-4.5V is cheaper at $0.60 / $1.80 per million input/output tokens, against $10 / $30 for GPT-4 Turbo.
  • GPT-4 Turbo accepts more context: 128K tokens versus 64K.
  • GLM-4.5V has downloadable open weights; the other is API-only.

Side by side

GLM-4.5VGPT-4 Turbo
ProviderZ.ai (Zhipu)OpenAI
Noometry Index39.830.5
Released2025-08-112023-11-06
WeightsOpenProprietary
Context window64K128K
Max output16K4K
Input $ / M tokens$0.60$10
Output $ / M tokens$1.80$30
Results tracked1536

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Category by category

Coding GLM-4.5V leads

GLM-4.5V: 39.5 (#155), GPT-4 Turbo: 33.8 (#249)

BenchmarkGLM-4.5VGPT-4 Turbo
LMArena Coding13471268
WeirdML—18%
BigCodeBench Instruct—48.2%
BigCodeBench Complete—58.2%
HumanEval+—86.6%
MBPP+—73.3%

Agentic & Tool Use Not comparable

GLM-4.5V: —, GPT-4 Turbo: —

BenchmarkGLM-4.5VGPT-4 Turbo
METR Time Horizons—36.7%

Reasoning GLM-4.5V leads

GLM-4.5V: 27.4 (#119), GPT-4 Turbo: 15.3 (#317)

BenchmarkGLM-4.5VGPT-4 Turbo
LMArena Hard Prompts13341251
SimpleBench—25.1%
Kagi LLM Benchmark59.8%—
Chess Puzzles—6%
DTBench—61.6%
LMCA—9.8%
Epoch Capabilities Index—127.25
ForecastBench—59.4

Math GLM-4.5V leads

GLM-4.5V: 37.4 (#159), GPT-4 Turbo: 9.0 (#322)

BenchmarkGLM-4.5VGPT-4 Turbo
LMArena Math13541272
FrontierMath (Tiers 1-3)—0.7%
OTIS Mock AIME 2024-2025—6.7%
MATH Level 5—46.7%

Knowledge GLM-4.5V leads

GLM-4.5V: 37.5 (#156), GPT-4 Turbo: 24.3 (#268)

BenchmarkGLM-4.5VGPT-4 Turbo
LMArena Expert13531223
GPQA Diamond—46.6%
Confabulations—28.4%
MMLU—81.3%

Multimodal GLM-4.5V leads

GLM-4.5V: 34.3 (#92), GPT-4 Turbo: 30.6 (#110)

BenchmarkGLM-4.5VGPT-4 Turbo
LMArena Vision11541090

Multilingual GLM-4.5V leads

GLM-4.5V: 44.6 (#177), GPT-4 Turbo: 40.5 (#216)

BenchmarkGLM-4.5VGPT-4 Turbo
LMArena Non-English13031245
LMArena Chinese13371242
LMArena Russian12981259
LMArena Spanish13361260
LMArena French—1276
LMArena German—1259
LMArena Japanese—1194
LMArena Korean—1187

Instruction Following GLM-4.5V leads

GLM-4.5V: 69.2 (#175), GPT-4 Turbo: 65.8 (#216)

BenchmarkGLM-4.5VGPT-4 Turbo
LMArena Instruction Following13111249

Long Context GLM-4.5V leads

GLM-4.5V: 39.6 (#171), GPT-4 Turbo: 38.0 (#206)

BenchmarkGLM-4.5VGPT-4 Turbo
LMArena Longer Query13041254

Writing & Preference GLM-4.5V leads

GLM-4.5V: 52.5 (#170), GPT-4 Turbo: 47.7 (#206)

BenchmarkGLM-4.5VGPT-4 Turbo
LMArena Text13331272
LMArena Creative Writing12951269
LMArena Multi-Turn13321267

Frequently asked questions

Is GLM-4.5V better than GPT-4 Turbo?

GLM-4.5V is the stronger model overall, scoring 39.8 to 30.5 on the Noometry Index.

Which is cheaper, GLM-4.5V or GPT-4 Turbo?

GLM-4.5V is cheaper. It lists at $0.60 per million input tokens and $1.80 per million output tokens; GPT-4 Turbo lists at $10 and $30.

Is GLM-4.5V or GPT-4 Turbo better for coding?

GLM-4.5V scores higher on coding benchmarks: 39.5 versus 33.8 in the Noometry coding category.

Which has the bigger context window?

GPT-4 Turbo does, with 128K tokens against 64K.

How many benchmarks do GLM-4.5V and GPT-4 Turbo share?

14 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and GPT-4 Turbo has 36.

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