Noometry

Model comparison

GLM-4.7 vs GPT-5.3 Chat

GLM-4.7 and GPT-5.3 Chat score almost the same on the Noometry Index (42.0 vs 42.8), so choose on price, context window or the category you care about most.

Last verified . 18 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

42.0

Rank #124 Confirmed

GPT-5.3 Chat OpenAI

42.8

Rank #109 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GLM-4.7 scores higher in 6 categories and GPT-5.3 Chat in 2 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.7 leads 47.0 to 38.8.
  • GLM-4.7 is cheaper at $0.60 / $2.20 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Chat.
  • GLM-4.7 accepts more context: 205K tokens versus 128K.
  • GLM-4.7 has downloadable open weights; the other is API-only.

Side by side

GLM-4.7GPT-5.3 Chat
ProviderZ.ai (Zhipu)OpenAI
Noometry Index42.042.8
Released2025-12-222026-03-03
WeightsOpenProprietary
Context window205K128K
Max output131K16K
Input $ / M tokens$0.60$1.75
Output $ / M tokens$2.20$14
Results tracked3618

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Category by category

Coding GLM-4.7 leads

GLM-4.7: 44.0 (#79), GPT-5.3 Chat: 41.4 (#124)

BenchmarkGLM-4.7GPT-5.3 Chat
LMArena Coding14541408
LMArena WebDev1435—
SciCode45.1%—
ALE-Bench399.48—

Agentic & Tool Use Not comparable

GLM-4.7: 26.5 (#103), GPT-5.3 Chat: —

BenchmarkGLM-4.7GPT-5.3 Chat
Terminal-Bench33.4%—
Vending-Bench 22,377—

Reasoning GPT-5.3 Chat leads

GLM-4.7: 24.3 (#164), GPT-5.3 Chat: 28.5 (#102)

BenchmarkGLM-4.7GPT-5.3 Chat
LMArena Hard Prompts14431399
SimpleBench47.7%—
CritPt1.7%—
Chess Puzzles6%—
Epoch Capabilities Index143.51—

Math Too close to call

GLM-4.7: 38.6 (#135), GPT-5.3 Chat: 38.2 (#142)

BenchmarkGLM-4.7GPT-5.3 Chat
LMArena Math14231389
OTIS Mock AIME 2024-202583.3%—
ProofBench6%—
FrontierMath (Feb 2025 set)2.4%—
FrontierMath Tier 4 (v1)0%—

Knowledge GLM-4.7 leads

GLM-4.7: 47.0 (#80), GPT-5.3 Chat: 38.8 (#140)

BenchmarkGLM-4.7GPT-5.3 Chat
LMArena Expert14241397
GPQA Diamond83.3%—
SimpleQA Verified32.2%—
Vectara Hallucination Rate11.7%—

Multilingual GLM-4.7 leads

GLM-4.7: 52.8 (#79), GPT-5.3 Chat: 50.3 (#124)

BenchmarkGLM-4.7GPT-5.3 Chat
LMArena Non-English14171382
LMArena Chinese14951432
LMArena French14321397
LMArena German14241384
LMArena Japanese14391352
LMArena Korean13991346
LMArena Russian14231400
LMArena Spanish14341371

Instruction Following GLM-4.7 leads

GLM-4.7: 74.4 (#95), GPT-5.3 Chat: 72.8 (#129)

BenchmarkGLM-4.7GPT-5.3 Chat
LMArena Instruction Following14111378

Long Context Too close to call

GLM-4.7: 42.8 (#116), GPT-5.3 Chat: 42.6 (#120)

BenchmarkGLM-4.7GPT-5.3 Chat
LMArena Longer Query14321396
CL-bench15.9%—
CL-bench Life10.9%—

Writing & Preference GPT-5.3 Chat leads

GLM-4.7: 60.9 (#93), GPT-5.3 Chat: 63.1 (#68)

BenchmarkGLM-4.7GPT-5.3 Chat
LMArena Text14351389
LMArena Creative Writing14011355
EQ-Bench Creative Writing14131690
LMArena Multi-Turn14461412

Frequently asked questions

Is GLM-4.7 better than GPT-5.3 Chat?

GLM-4.7 and GPT-5.3 Chat score almost the same on the Noometry Index (42.0 vs 42.8), so choose on price, context window or the category you care about most.

Which is cheaper, GLM-4.7 or GPT-5.3 Chat?

GLM-4.7 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; GPT-5.3 Chat lists at $1.75 and $14.

Is GLM-4.7 or GPT-5.3 Chat better for coding?

GLM-4.7 scores higher on coding benchmarks: 44.0 versus 41.4 in the Noometry coding category.

Which has the bigger context window?

GLM-4.7 does, with 205K tokens against 128K.

How many benchmarks do GLM-4.7 and GPT-5.3 Chat share?

18 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and GPT-5.3 Chat has 18.

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