Noometry

Model comparison

GLM-5.3 vs GPT-4

GLM-5.3 is the stronger model overall, scoring 54.8 to 29.1 on the Noometry Index.

Last verified . 26 shared benchmarks.

GLM-5.3 Z.ai (Zhipu)

54.8

Rank #26 Confirmed

GPT-4 OpenAI

29.1

Rank #316 Confirmed

Summary

  • They share 26 benchmarks with published results for both. GLM-5.3 scores higher in 8 categories and GPT-4 in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-5.3 leads 62.3 to 10.8.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 91.1% for GLM-5.3 and 1.1% for GPT-4.
  • GLM-5.3 is cheaper at $1.40 / $4.40 per million input/output tokens, against $30 / $60 for GPT-4.
  • GLM-5.3 accepts more context: 1M tokens versus 8K.
  • GLM-5.3 has downloadable open weights; the other is API-only.

Side by side

GLM-5.3GPT-4
ProviderZ.ai (Zhipu)OpenAI
Noometry Index54.829.1
Released2026-08-142023-03-14
WeightsOpenProprietary
Context window1M8K
Max output131K8K
Input $ / M tokens$1.40$30
Output $ / M tokens$4.40$60
Results tracked4238

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Category by category

Coding GLM-5.3 leads

GLM-5.3: 59.5 (#14), GPT-4: 31.6 (#283)

BenchmarkGLM-5.3GPT-4
WeirdML75.4%12.4%
LMArena Coding14961254
DeepSWE69%—
FrontierCode40.1%—
CursorBench42.6%—
LMArena WebDev1622—
FrontierSWE30.2%—
SciCode59%—
BigCodeBench Instruct—46%
BigCodeBench Complete—57.2%
ALE-Bench1,317—
HumanEval+—79.3%

Agentic & Tool Use Not comparable

GLM-5.3: 36.4 (#38), GPT-4: —

BenchmarkGLM-5.3GPT-4
APEX-Agents56.6%—
METR Time Horizons—36.1%
Vending-Bench 28,164—

Reasoning GLM-5.3 leads

GLM-5.3: 46.1 (#46), GPT-4: 17.8 (#289)

BenchmarkGLM-5.3GPT-4
Chess Puzzles21%4%
LMArena Hard Prompts14891241
Mystery Game Puzzles33%12%
DTBench87.7%62.7%
LMCA55.5%17.1%
Epoch Capabilities Index155.61125.89
NYT Connections (extended)74.2%—
CritPt19.1%—
Bench to the Future 30.15—
BIG-Bench Hard—75.1%
ForecastBench—57.8
HellaSwag—95.3%
WinoGrande—87.5%

Math GLM-5.3 leads

GLM-5.3: 62.3 (#33), GPT-4: 10.8 (#309)

BenchmarkGLM-5.3GPT-4
OTIS Mock AIME 2024-202591.1%1.1%
LMArena Math14891269
FrontierMath (Tiers 1-3)68.8%—
FrontierMath Tier 429.3%—
ProofBench49%—
MATH Level 5—23%
GSM8K—92%

Knowledge GLM-5.3 leads

GLM-5.3: 58.3 (#37), GPT-4: 18.4 (#282)

BenchmarkGLM-5.3GPT-4
GPQA Diamond90.9%35.7%
LMArena Expert15161211
SimpleQA Verified41%—
MMLU—86.4%
TriviaQA—84.8%

Multilingual GLM-5.3 leads

GLM-5.3: 55.7 (#28), GPT-4: 40.6 (#215)

BenchmarkGLM-5.3GPT-4
LMArena Non-English14571246
LMArena Chinese15281242
LMArena French14991283
LMArena German14991251
LMArena Japanese14531209
LMArena Korean14721184
LMArena Russian14631251
LMArena Spanish14601261

Instruction Following GLM-5.3 leads

GLM-5.3: 77.5 (#23), GPT-4: 65.3 (#222)

BenchmarkGLM-5.3GPT-4
LMArena Instruction Following14771241

Long Context GLM-5.3 leads

GLM-5.3: 45.4 (#41), GPT-4: 37.7 (#212)

BenchmarkGLM-5.3GPT-4
LMArena Longer Query14821244

Writing & Preference GLM-5.3 leads

GLM-5.3: 75.7 (#6), GPT-4: 34.9 (#268)

BenchmarkGLM-5.3GPT-4
LMArena Text14711263
LMArena Creative Writing14571244
EQ-Bench Creative Writing2075752
LMArena Multi-Turn14721257

Frequently asked questions

Is GLM-5.3 better than GPT-4?

GLM-5.3 is the stronger model overall, scoring 54.8 to 29.1 on the Noometry Index.

Which is cheaper, GLM-5.3 or GPT-4?

GLM-5.3 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; GPT-4 lists at $30 and $60.

Is GLM-5.3 or GPT-4 better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.5 versus 31.6 in the Noometry coding category.

Which has the bigger context window?

GLM-5.3 does, with 1M tokens against 8K.

How many benchmarks do GLM-5.3 and GPT-4 share?

26 benchmarks have published results for both models. GLM-5.3 has 42 scored results on Noometry and GPT-4 has 38.

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