Noometry

Model comparison

GLM-5.3-Flash vs GPT-4o mini

GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 25.4 on the Noometry Index.

Last verified . 24 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

49.6

Rank #45 Confirmed

GPT-4o mini OpenAI

25.4

Rank #337 Confirmed

Summary

  • They share 24 benchmarks with published results for both. GLM-5.3-Flash scores higher in 10 categories and GPT-4o mini in 0 categories; 10 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-5.3-Flash leads 53.1 to 9.9.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 93.9% for GLM-5.3-Flash and 6.9% for GPT-4o mini.
  • GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $0.15 / $0.60 for GPT-4o mini.
  • GLM-5.3-Flash accepts more context: 1M tokens versus 128K.
  • GLM-5.3-Flash has downloadable open weights; the other is API-only.

Side by side

GLM-5.3-FlashGPT-4o mini
ProviderZ.ai (Zhipu)OpenAI
Noometry Index49.625.4
Released2026-08-202024-07-18
WeightsOpenProprietary
Context window1M128K
Max output131K16K
Input $ / M tokens$0.15$0.15
Output $ / M tokens$0.50$0.60
Results tracked3660

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding GLM-5.3-Flash leads

GLM-5.3-Flash: 53.7 (#26), GPT-4o mini: 21.6 (#330)

BenchmarkGLM-5.3-FlashGPT-4o mini
LMArena Coding15061290
DeepSWE63.4%—
FrontierCode31.8%—
Aider Polyglot—3.6%
LMArena WebDev1614—
SciCode51.6%—
WeirdML—11.8%
BigCodeBench Instruct—46.1%
LiveBench Coding—43.1%
BigCodeBench Complete—57.4%
ALE-Bench303.55—
HumanEval+—83.5%
MBPP+—72.2%

Agentic & Tool Use GLM-5.3-Flash leads

GLM-5.3-Flash: 34.3 (#41), GPT-4o mini: 27.2 (#95)

BenchmarkGLM-5.3-FlashGPT-4o mini
APEX-Agents52.8%—
BALROG—17.4%
GDP.pdf14%—

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 31.7 (#69), GPT-4o mini: 8.7 (#343)

BenchmarkGLM-5.3-FlashGPT-4o mini
Chess Puzzles14%0%
LMArena Hard Prompts14901267
Mystery Game Puzzles8%12%
Epoch Capabilities Index151.9126.56
ARC-AGI-2—0%
SimpleBench—10.7%
Kagi LLM Benchmark—28.8%
CritPt15.4%—
LiveBench Reasoning—32.8%
DTBench—54.4%
LiveBench Data Analysis—50%
LMCA—10.4%
Surface Evolver Bench52.5%—
Bench to the Future 30.15—
LiveBench—41.3%
PIQA—88.7%

Math GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#38), GPT-4o mini: 9.9 (#307)

BenchmarkGLM-5.3-FlashGPT-4o mini
FrontierMath (Tiers 1-3)55.8%0.7%
OTIS Mock AIME 2024-202593.9%6.9%
LMArena Math14991267
FrontierMath Tier 417.1%—
ProofBench21%—
Omni-MATH—28%
LiveBench Math—36.3%
MATH Level 5—52.6%
GSM8K—91.3%

Knowledge GLM-5.3-Flash leads

GLM-5.3-Flash: 58.4 (#33), GPT-4o mini: 17.7 (#279)

BenchmarkGLM-5.3-FlashGPT-4o mini
GPQA Diamond90.2%37.7%
LMArena Expert15121235
SimpleQA Verified—8.3%
MMLU-Pro—60.3%
Confabulations—37.2%
GPQA (HELM)—36.8%
BoolQ—88.7%
MMLU—81.8%

Multimodal GLM-5.3-Flash leads

GLM-5.3-Flash: 42.6 (#25), GPT-4o mini: 25.3 (#117)

BenchmarkGLM-5.3-FlashGPT-4o mini
LMArena Vision13041066
Video-MME—64.8%
GeoBench—64%
VPCT—34%

Multilingual GLM-5.3-Flash leads

GLM-5.3-Flash: 56.2 (#24), GPT-4o mini: 42.2 (#194)

BenchmarkGLM-5.3-FlashGPT-4o mini
LMArena Non-English14621266
LMArena Chinese15291264
LMArena French14951296
LMArena German14571272
LMArena Japanese14201216
LMArena Korean14431195
LMArena Russian14721275
LMArena Spanish14711276

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.8 (#17), GPT-4o mini: 62.1 (#234)

BenchmarkGLM-5.3-FlashGPT-4o mini
LMArena Instruction Following14801259
LiveBench Instruction Following—56.8%
IFEval—78.2%

Long Context GLM-5.3-Flash leads

GLM-5.3-Flash: 45.3 (#41), GPT-4o mini: 39.1 (#181)

BenchmarkGLM-5.3-FlashGPT-4o mini
LMArena Longer Query14791289

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.4 (#49), GPT-4o mini: 39.7 (#243)

BenchmarkGLM-5.3-FlashGPT-4o mini
LMArena Text14711286
LMArena Creative Writing14401268
LMArena Multi-Turn14711285
Short-Story Creative Writing—67.2%
EQ-Bench Creative Writing—873
WildBench—79.1%
LiveBench Language—28.6%

Frequently asked questions

Is GLM-5.3-Flash better than GPT-4o mini?

GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 25.4 on the Noometry Index.

Which is cheaper, GLM-5.3-Flash or GPT-4o mini?

GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; GPT-4o mini lists at $0.15 and $0.60.

Is GLM-5.3-Flash or GPT-4o mini better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.7 versus 21.6 in the Noometry coding category.

Which has the bigger context window?

GLM-5.3-Flash does, with 1M tokens against 128K.

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

24 benchmarks have published results for both models. GLM-5.3-Flash has 36 scored results on Noometry and GPT-4o mini has 60.

Related comparisons

Go deeper