Noometry

Model comparison

GLM-5.3-Flash vs GPT-6 Luna

GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 45.1 on the Noometry Index.

Last verified . 16 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

49.6

Rank #45 Confirmed

GPT-6 Luna OpenAI

45.1

Rank #65 Confirmed

Summary

  • They share 16 benchmarks with published results for both. GLM-5.3-Flash scores higher in 7 categories and GPT-6 Luna in 2 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-5.3-Flash leads 58.4 to 40.1.
  • The biggest single-benchmark swing is FrontierCode: 31.8% for GLM-5.3-Flash and 42.4% for GPT-6 Luna.
  • GPT-6 Luna is cheaper at $0.10 / $0.50 per million input/output tokens, against $0.15 / $0.50 for GLM-5.3-Flash.
  • GPT-6 Luna 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-6 Luna
ProviderZ.ai (Zhipu)OpenAI
Noometry Index49.645.1
Released2026-08-202026-09-22
WeightsOpenProprietary
Context window1M1.05M
Max output131K128K
Input $ / M tokens$0.15$0.10
Output $ / M tokens$0.50$0.50
Results tracked3618

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Category by category

Coding Too close to call

GLM-5.3-Flash: 53.7 (#26), GPT-6 Luna: 54.7 (#24)

BenchmarkGLM-5.3-FlashGPT-6 Luna
DeepSWE63.4%66.6%
FrontierCode31.8%42.4%
LMArena WebDev16141583
LMArena Coding15061448
SciCode51.6%—
ALE-Bench303.55—

Agentic & Tool Use Not comparable

GLM-5.3-Flash: 34.3 (#41), GPT-6 Luna: —

BenchmarkGLM-5.3-FlashGPT-6 Luna
APEX-Agents52.8%—
GDP.pdf14%—

Reasoning Too close to call

GLM-5.3-Flash: 31.7 (#69), GPT-6 Luna: 31.7 (#68)

BenchmarkGLM-5.3-FlashGPT-6 Luna
LMArena Hard Prompts14901415
NYT Connections (extended)—68.7%
CritPt15.4%—
Chess Puzzles14%—
Mystery Game Puzzles8%—
Surface Evolver Bench52.5%—
Bench to the Future 30.15—
Epoch Capabilities Index151.9—

Math GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#38), GPT-6 Luna: 35.6 (#140)

BenchmarkGLM-5.3-FlashGPT-6 Luna
LMArena Math14991396
FrontierMath (Tiers 1-3)55.8%—
FrontierMath Tier 417.1%—
OTIS Mock AIME 2024-202593.9%—
ProofBench21%—

Knowledge GLM-5.3-Flash leads

GLM-5.3-Flash: 58.4 (#33), GPT-6 Luna: 40.1 (#110)

BenchmarkGLM-5.3-FlashGPT-6 Luna
LMArena Expert15121458
GPQA Diamond90.2%—

Multimodal Too close to call

GLM-5.3-Flash: 42.6 (#25), GPT-6 Luna: 42.0 (#27)

BenchmarkGLM-5.3-FlashGPT-6 Luna
LMArena Vision1304—
Furniture Assembly—44.2%

Multilingual GLM-5.3-Flash leads

GLM-5.3-Flash: 56.2 (#24), GPT-6 Luna: 51.0 (#111)

BenchmarkGLM-5.3-FlashGPT-6 Luna
LMArena Non-English14621390
LMArena Chinese15291425
LMArena Russian14721392
LMArena Spanish14711416
LMArena French1495—
LMArena German1457—
LMArena Japanese1420—
LMArena Korean1443—

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.8 (#17), GPT-6 Luna: 74.7 (#85)

BenchmarkGLM-5.3-FlashGPT-6 Luna
LMArena Instruction Following14801414

Long Context GLM-5.3-Flash leads

GLM-5.3-Flash: 45.3 (#41), GPT-6 Luna: 43.3 (#95)

BenchmarkGLM-5.3-FlashGPT-6 Luna
LMArena Longer Query14791417

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.4 (#49), GPT-6 Luna: 58.4 (#115)

BenchmarkGLM-5.3-FlashGPT-6 Luna
LMArena Text14711392
LMArena Creative Writing14401357
LMArena Multi-Turn14711400

Frequently asked questions

Is GLM-5.3-Flash better than GPT-6 Luna?

GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 45.1 on the Noometry Index.

Which is cheaper, GLM-5.3-Flash or GPT-6 Luna?

GPT-6 Luna is cheaper. It lists at $0.10 per million input tokens and $0.50 per million output tokens; GLM-5.3-Flash lists at $0.15 and $0.50.

Is GLM-5.3-Flash or GPT-6 Luna better for coding?

They score almost the same on coding (53.7 vs 54.7); test both on your own repository before choosing.

Which has the bigger context window?

GPT-6 Luna does, with 1.05M tokens against 1M.

How many benchmarks do GLM-5.3-Flash and GPT-6 Luna share?

16 benchmarks have published results for both models. GLM-5.3-Flash has 36 scored results on Noometry and GPT-6 Luna has 18.

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