Noometry

Model comparison

GLM-5.3-Flash vs GPT-4.1

GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 35.7 on the Noometry Index.

Last verified . 24 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

49.6

Rank #45 Confirmed

GPT-4.1 OpenAI

35.7

Rank #215 Confirmed

Summary

  • They share 24 benchmarks with published results for both. GLM-5.3-Flash scores higher in 9 categories and GPT-4.1 in 1 category; 9 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-5.3-Flash leads 53.1 to 21.4.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 93.9% for GLM-5.3-Flash and 38.3% for GPT-4.1.
  • GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $2 / $8 for GPT-4.1.
  • GPT-4.1 accepts more context: 1.05M tokens versus 1M.
  • GLM-5.3-Flash has downloadable open weights; the other is API-only.

Side by side

GLM-5.3-FlashGPT-4.1
ProviderZ.ai (Zhipu)OpenAI
Noometry Index49.635.7
Released2026-08-202025-04-14
WeightsOpenProprietary
Context window1M1.05M
Max output131K33K
Input $ / M tokens$0.15$2
Output $ / M tokens$0.50$8
Results tracked3652

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Category by category

Coding GLM-5.3-Flash leads

GLM-5.3-Flash: 53.7 (#26), GPT-4.1: 34.2 (#228)

BenchmarkGLM-5.3-FlashGPT-4.1
LMArena Coding15061391
ALE-Bench303.55558.1
SWE-bench Verified—48.5%
DeepSWE63.4%—
FrontierCode31.8%—
SWE-bench Verified (bash only)—39.6%
Aider Polyglot—52.4%
LMArena WebDev1614—
SciCode51.6%—
WeirdML—39%
CadEval—42%

Agentic & Tool Use Too close to call

GLM-5.3-Flash: 34.3 (#41), GPT-4.1: 34.4 (#40)

BenchmarkGLM-5.3-FlashGPT-4.1
APEX-Agents52.8%—
Berkeley Function Calling Leaderboard—54%
GDP.pdf14%—

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 31.7 (#69), GPT-4.1: 11.7 (#334)

BenchmarkGLM-5.3-FlashGPT-4.1
Chess Puzzles14%6%
LMArena Hard Prompts14901384
Epoch Capabilities Index151.9136.79
ARC-AGI-2—0.4%
SimpleBench—27%
Kagi LLM Benchmark—52.3%
ARC-AGI-1—5.5%
CritPt15.4%—
EnigmaEval—2.2%
Mystery Game Puzzles8%—
DTBench—68.3%
LMCA—25.6%
Surface Evolver Bench52.5%—
Bench to the Future 30.15—
ForecastBench—61.5

Math GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#38), GPT-4.1: 21.4 (#269)

BenchmarkGLM-5.3-FlashGPT-4.1
FrontierMath (Tiers 1-3)55.8%6%
OTIS Mock AIME 2024-202593.9%38.3%
LMArena Math14991369
FrontierMath Tier 417.1%—
ProofBench21%—
Omni-MATH—47.1%
MATH Level 5—83%
FrontierMath (Feb 2025 set)—5.5%
FrontierMath Tier 4 (v1)—0%

Knowledge GLM-5.3-Flash leads

GLM-5.3-Flash: 58.4 (#33), GPT-4.1: 37.0 (#152)

BenchmarkGLM-5.3-FlashGPT-4.1
GPQA Diamond90.2%66.9%
LMArena Expert15121364
Humanity's Last Exam—5.4%
SimpleQA Verified—31.1%
MMLU-Pro—81.1%
Vectara Hallucination Rate—5.6%
GPQA (HELM)—65.9%

Multimodal GLM-5.3-Flash leads

GLM-5.3-Flash: 42.6 (#25), GPT-4.1: 37.5 (#66)

BenchmarkGLM-5.3-FlashGPT-4.1
LMArena Vision13041210
GeoBench—72%

Multilingual GLM-5.3-Flash leads

GLM-5.3-Flash: 56.2 (#24), GPT-4.1: 49.6 (#128)

BenchmarkGLM-5.3-FlashGPT-4.1
LMArena Non-English14621370
LMArena Chinese15291382
LMArena French14951383
LMArena German14571380
LMArena Japanese14201320
LMArena Korean14431339
LMArena Russian14721377
LMArena Spanish14711375

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.8 (#17), GPT-4.1: 71.5 (#148)

BenchmarkGLM-5.3-FlashGPT-4.1
LMArena Instruction Following14801367
IFEval—83.8%

Long Context GLM-5.3-Flash leads

GLM-5.3-Flash: 45.3 (#41), GPT-4.1: 40.0 (#158)

BenchmarkGLM-5.3-FlashGPT-4.1
LMArena Longer Query14791385
Fiction.LiveBench—63.9%

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.4 (#49), GPT-4.1: 57.8 (#120)

BenchmarkGLM-5.3-FlashGPT-4.1
LMArena Text14711383
LMArena Creative Writing14401363
LMArena Multi-Turn14711398
EQ-Bench Creative Writing—1420
WildBench—85.4%

Frequently asked questions

Is GLM-5.3-Flash better than GPT-4.1?

GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 35.7 on the Noometry Index.

Which is cheaper, GLM-5.3-Flash or GPT-4.1?

GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; GPT-4.1 lists at $2 and $8.

Is GLM-5.3-Flash or GPT-4.1 better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.7 versus 34.2 in the Noometry coding category.

Which has the bigger context window?

GPT-4.1 does, with 1.05M tokens against 1M.

How many benchmarks do GLM-5.3-Flash and GPT-4.1 share?

24 benchmarks have published results for both models. GLM-5.3-Flash has 36 scored results on Noometry and GPT-4.1 has 52.

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