Noometry

Model comparison

GLM-4.7-Flash vs GLM-5.3-Flash

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 1.6× less per token, which makes it the better buy when GLM-5.3-Flash's lead doesn't matter for your workload.

Last verified . 19 shared benchmarks.

GLM-4.7-Flash Z.ai (Zhipu)

38.8

Rank #180 Confirmed

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

Summary

  • They share 19 benchmarks with published results for both. GLM-4.7-Flash scores higher in 0 categories and GLM-5.3-Flash in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-5.3-Flash leads 48.0 to 20.9.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 58.3% for GLM-4.7-Flash and 93.9% for GLM-5.3-Flash.
  • GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.15 / $0.50 for GLM-5.3-Flash.
  • GLM-5.3-Flash accepts more context: 1M tokens versus 200K.

Side by side

GLM-4.7-FlashGLM-5.3-Flash
ProviderZ.ai (Zhipu)Z.ai (Zhipu)
Noometry Index38.851.8
Released2026-01-192026-08-20
WeightsOpenOpen
Context window200K1M
Max output131K131K
Input $ / M tokens$0.06$0.15
Output $ / M tokens$0.40$0.50
Results tracked2140

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Category by category

Coding GLM-5.3-Flash leads

GLM-4.7-Flash: 40.6 (#135), GLM-5.3-Flash: 53.1 (#31)

BenchmarkGLM-4.7-FlashGLM-5.3-Flash
LMArena Coding13831508
DeepSWE—63.4%
FrontierCode—31.8%
CursorBench—36.8%
LMArena WebDev—1609
FrontierSWE—18.1%
SciCode—51.6%
ALE-Bench—303.55

Agentic & Tool Use Not comparable

GLM-4.7-Flash: —, GLM-5.3-Flash: 34.2 (#47)

BenchmarkGLM-4.7-FlashGLM-5.3-Flash
APEX-Agents—52.8%
GDP.pdf—14%

Reasoning GLM-5.3-Flash leads

GLM-4.7-Flash: 20.9 (#229), GLM-5.3-Flash: 48.0 (#42)

BenchmarkGLM-4.7-FlashGLM-5.3-Flash
Chess Puzzles0%14%
LMArena Hard Prompts13561491
ARC-AGI-2—65.8%
ARC-AGI-1—91%
CritPt—15.4%
Mystery Game Puzzles—8%
Surface Evolver Bench—52.5%
Bench to the Future 3—0.15
Epoch Capabilities Index—151.88

Math GLM-5.3-Flash leads

GLM-4.7-Flash: 36.1 (#173), GLM-5.3-Flash: 53.3 (#47)

BenchmarkGLM-4.7-FlashGLM-5.3-Flash
OTIS Mock AIME 2024-202558.3%93.9%
LMArena Math13551500
FrontierMath (Tiers 1-3)—55.8%
FrontierMath Tier 4—17.1%
ProofBench—21%

Knowledge GLM-5.3-Flash leads

GLM-4.7-Flash: 35.5 (#184), GLM-5.3-Flash: 58.4 (#36)

BenchmarkGLM-4.7-FlashGLM-5.3-Flash
GPQA Diamond60.5%90.2%
LMArena Expert13571513
Vectara Hallucination Rate9.3%—

Multimodal Not comparable

GLM-4.7-Flash: —, GLM-5.3-Flash: 42.8 (#27)

BenchmarkGLM-4.7-FlashGLM-5.3-Flash
LMArena Vision—1296

Multilingual GLM-5.3-Flash leads

GLM-4.7-Flash: 46.5 (#158), GLM-5.3-Flash: 56.0 (#25)

BenchmarkGLM-4.7-FlashGLM-5.3-Flash
LMArena Non-English13301462
LMArena Chinese14031527
LMArena French13321496
LMArena German13371470
LMArena Korean12831446
LMArena Russian13321469
LMArena Spanish13501471
LMArena Japanese—1429

Instruction Following GLM-5.3-Flash leads

GLM-4.7-Flash: 70.1 (#167), GLM-5.3-Flash: 77.5 (#20)

BenchmarkGLM-4.7-FlashGLM-5.3-Flash
LMArena Instruction Following13271478

Long Context GLM-5.3-Flash leads

GLM-4.7-Flash: 40.9 (#148), GLM-5.3-Flash: 45.4 (#39)

BenchmarkGLM-4.7-FlashGLM-5.3-Flash
LMArena Longer Query13451482

Writing & Preference GLM-5.3-Flash leads

GLM-4.7-Flash: 47.4 (#210), GLM-5.3-Flash: 65.3 (#50)

BenchmarkGLM-4.7-FlashGLM-5.3-Flash
LMArena Text13511471
LMArena Creative Writing12971442
LMArena Multi-Turn13421467
EQ-Bench Creative Writing1125—

Frequently asked questions

Is GLM-4.7-Flash better than GLM-5.3-Flash?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 1.6× less per token, which makes it the better buy when GLM-5.3-Flash's lead doesn't matter for your workload.

Which is cheaper, GLM-4.7-Flash or GLM-5.3-Flash?

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; GLM-5.3-Flash lists at $0.15 and $0.50.

Is GLM-4.7-Flash or GLM-5.3-Flash better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 40.6 in the Noometry coding category.

Which has the bigger context window?

GLM-5.3-Flash does, with 1M tokens against 200K.

How many benchmarks do GLM-4.7-Flash and GLM-5.3-Flash share?

19 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and GLM-5.3-Flash has 40.

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