Noometry

Model comparison

GLM-4.7-Flash vs GPT-6 Luna

GPT-6 Luna is the stronger model overall, scoring 53.3 to 38.8 on the Noometry Index.

Last verified . 19 shared benchmarks.

GLM-4.7-Flash Z.ai (Zhipu)

38.8

Rank #180 Confirmed

GPT-6 Luna OpenAI

53.3

Rank #36 Confirmed

Summary

  • They share 19 benchmarks with published results for both. GLM-4.7-Flash scores higher in 0 categories and GPT-6 Luna in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where GPT-6 Luna leads 76.1 to 36.1.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 58.3% for GLM-4.7-Flash and 98.9% for GPT-6 Luna.
  • GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.10 / $0.50 for GPT-6 Luna.
  • GPT-6 Luna accepts more context: 1.05M tokens versus 200K.
  • GLM-4.7-Flash has downloadable open weights; the other is API-only.

Side by side

GLM-4.7-FlashGPT-6 Luna
ProviderZ.ai (Zhipu)OpenAI
Noometry Index38.853.3
Released2026-01-192026-09-22
WeightsOpenProprietary
Context window200K1.05M
Max output131K128K
Input $ / M tokens$0.06$0.10
Output $ / M tokens$0.40$0.50
Results tracked2142

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Category by category

Coding GPT-6 Luna leads

GLM-4.7-Flash: 40.6 (#135), GPT-6 Luna: 55.5 (#25)

BenchmarkGLM-4.7-FlashGPT-6 Luna
LMArena Coding13831439
DeepSWE—66.6%
FrontierCode—42.4%
LMArena WebDev—1581
SciCode—54.6%
ALE-Bench—1,577

Agentic & Tool Use Not comparable

GLM-4.7-Flash: —, GPT-6 Luna: 33.3 (#54)

BenchmarkGLM-4.7-FlashGPT-6 Luna
APEX-Agents—44.3%
GDP.pdf—23%

Reasoning GPT-6 Luna leads

GLM-4.7-Flash: 20.9 (#229), GPT-6 Luna: 48.2 (#41)

BenchmarkGLM-4.7-FlashGPT-6 Luna
Chess Puzzles0%31%
LMArena Hard Prompts13561411
ARC-AGI-2—59.3%
NYT Connections (extended)—68.7%
ARC-AGI-1—86.7%
CritPt—19.4%
Mystery Game Puzzles—7%
DTBench—90.1%
LMCA—44.5%
Epoch Capabilities Index—156.28

Math GPT-6 Luna leads

GLM-4.7-Flash: 36.1 (#173), GPT-6 Luna: 76.1 (#15)

BenchmarkGLM-4.7-FlashGPT-6 Luna
OTIS Mock AIME 2024-202558.3%98.9%
LMArena Math13551416
FrontierMath (Tiers 1-3)—78.9%
FrontierMath Tier 4—56.1%
ProofBench—64%

Knowledge GPT-6 Luna leads

GLM-4.7-Flash: 35.5 (#184), GPT-6 Luna: 57.0 (#41)

BenchmarkGLM-4.7-FlashGPT-6 Luna
GPQA Diamond60.5%90.5%
LMArena Expert13571444
SimpleQA Verified—41.4%
Vectara Hallucination Rate9.3%—

Multimodal Not comparable

GLM-4.7-Flash: —, GPT-6 Luna: 42.4 (#30)

BenchmarkGLM-4.7-FlashGPT-6 Luna
LMArena Vision—1217
Blueprint-Bench 2—31.2%
Furniture Assembly—44.2%

Multilingual GPT-6 Luna leads

GLM-4.7-Flash: 46.5 (#158), GPT-6 Luna: 50.5 (#117)

BenchmarkGLM-4.7-FlashGPT-6 Luna
LMArena Non-English13301386
LMArena Chinese14031433
LMArena French13321420
LMArena German13371369
LMArena Korean12831360
LMArena Russian13321394
LMArena Spanish13501393
LMArena Japanese—1369

Instruction Following GPT-6 Luna leads

GLM-4.7-Flash: 70.1 (#167), GPT-6 Luna: 74.3 (#99)

BenchmarkGLM-4.7-FlashGPT-6 Luna
LMArena Instruction Following13271409

Long Context GPT-6 Luna leads

GLM-4.7-Flash: 40.9 (#148), GPT-6 Luna: 43.0 (#111)

BenchmarkGLM-4.7-FlashGPT-6 Luna
LMArena Longer Query13451409

Writing & Preference GPT-6 Luna leads

GLM-4.7-Flash: 47.4 (#210), GPT-6 Luna: 58.3 (#119)

BenchmarkGLM-4.7-FlashGPT-6 Luna
LMArena Text13511391
LMArena Creative Writing12971363
LMArena Multi-Turn13421396
EQ-Bench Creative Writing1125—

Frequently asked questions

Is GLM-4.7-Flash better than GPT-6 Luna?

GPT-6 Luna is the stronger model overall, scoring 53.3 to 38.8 on the Noometry Index.

Which is cheaper, GLM-4.7-Flash or GPT-6 Luna?

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; GPT-6 Luna lists at $0.10 and $0.50.

Is GLM-4.7-Flash or GPT-6 Luna better for coding?

GPT-6 Luna scores higher on coding benchmarks: 55.5 versus 40.6 in the Noometry coding category.

Which has the bigger context window?

GPT-6 Luna does, with 1.05M tokens against 200K.

How many benchmarks do GLM-4.7-Flash and GPT-6 Luna share?

19 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and GPT-6 Luna has 42.

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