Noometry

Model comparison

GLM-5.3 vs GPT-5.3 Chat

GLM-5.3 is the stronger model overall, scoring 54.8 to 42.8 on the Noometry Index.

Last verified . 18 shared benchmarks.

GLM-5.3 Z.ai (Zhipu)

54.8

Rank #26 Confirmed

GPT-5.3 Chat OpenAI

42.8

Rank #109 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GLM-5.3 scores higher in 8 categories and GPT-5.3 Chat in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-5.3 leads 62.3 to 38.2.
  • GLM-5.3 is cheaper at $1.40 / $4.40 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Chat.
  • GLM-5.3 accepts more context: 1M tokens versus 128K.
  • GLM-5.3 has downloadable open weights; the other is API-only.

Side by side

GLM-5.3GPT-5.3 Chat
ProviderZ.ai (Zhipu)OpenAI
Noometry Index54.842.8
Released2026-08-142026-03-03
WeightsOpenProprietary
Context window1M128K
Max output131K16K
Input $ / M tokens$1.40$1.75
Output $ / M tokens$4.40$14
Results tracked4218

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Category by category

Coding GLM-5.3 leads

GLM-5.3: 59.5 (#14), GPT-5.3 Chat: 41.4 (#124)

BenchmarkGLM-5.3GPT-5.3 Chat
LMArena Coding14961408
DeepSWE69%—
FrontierCode40.1%—
CursorBench42.6%—
LMArena WebDev1622—
FrontierSWE30.2%—
SciCode59%—
WeirdML75.4%—
ALE-Bench1,317—

Agentic & Tool Use Not comparable

GLM-5.3: 36.4 (#38), GPT-5.3 Chat: —

BenchmarkGLM-5.3GPT-5.3 Chat
APEX-Agents56.6%—
Vending-Bench 28,164—

Reasoning GLM-5.3 leads

GLM-5.3: 46.1 (#46), GPT-5.3 Chat: 28.5 (#102)

BenchmarkGLM-5.3GPT-5.3 Chat
LMArena Hard Prompts14891399
NYT Connections (extended)74.2%—
CritPt19.1%—
Chess Puzzles21%—
Mystery Game Puzzles33%—
DTBench87.7%—
LMCA55.5%—
Bench to the Future 30.15—
Epoch Capabilities Index155.61—

Math GLM-5.3 leads

GLM-5.3: 62.3 (#33), GPT-5.3 Chat: 38.2 (#142)

BenchmarkGLM-5.3GPT-5.3 Chat
LMArena Math14891389
FrontierMath (Tiers 1-3)68.8%—
FrontierMath Tier 429.3%—
OTIS Mock AIME 2024-202591.1%—
ProofBench49%—

Knowledge GLM-5.3 leads

GLM-5.3: 58.3 (#37), GPT-5.3 Chat: 38.8 (#140)

BenchmarkGLM-5.3GPT-5.3 Chat
LMArena Expert15161397
GPQA Diamond90.9%—
SimpleQA Verified41%—

Multilingual GLM-5.3 leads

GLM-5.3: 55.7 (#28), GPT-5.3 Chat: 50.3 (#124)

BenchmarkGLM-5.3GPT-5.3 Chat
LMArena Non-English14571382
LMArena Chinese15281432
LMArena French14991397
LMArena German14991384
LMArena Japanese14531352
LMArena Korean14721346
LMArena Russian14631400
LMArena Spanish14601371

Instruction Following GLM-5.3 leads

GLM-5.3: 77.5 (#23), GPT-5.3 Chat: 72.8 (#129)

BenchmarkGLM-5.3GPT-5.3 Chat
LMArena Instruction Following14771378

Long Context GLM-5.3 leads

GLM-5.3: 45.4 (#41), GPT-5.3 Chat: 42.6 (#120)

BenchmarkGLM-5.3GPT-5.3 Chat
LMArena Longer Query14821396

Writing & Preference GLM-5.3 leads

GLM-5.3: 75.7 (#6), GPT-5.3 Chat: 63.1 (#68)

BenchmarkGLM-5.3GPT-5.3 Chat
LMArena Text14711389
LMArena Creative Writing14571355
EQ-Bench Creative Writing20751690
LMArena Multi-Turn14721412

Frequently asked questions

Is GLM-5.3 better than GPT-5.3 Chat?

GLM-5.3 is the stronger model overall, scoring 54.8 to 42.8 on the Noometry Index.

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

GLM-5.3 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; GPT-5.3 Chat lists at $1.75 and $14.

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

GLM-5.3 scores higher on coding benchmarks: 59.5 versus 41.4 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-5.3 and GPT-5.3 Chat share?

18 benchmarks have published results for both models. GLM-5.3 has 42 scored results on Noometry and GPT-5.3 Chat has 18.

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