Model comparison

GLM-4.5V vs GLM-4.7-Flash

GLM-4.5V and GLM-4.7-Flash score almost the same on the Noometry Index (39.8 vs 38.8), so choose on price, context window or the category you care about most.

Last verified . 13 shared benchmarks.

GLM-4.5V Z.ai (Zhipu)

39.8

Rank #158 Confirmed

GLM-4.7-Flash Z.ai (Zhipu)

38.8

Rank #180 Confirmed

Summary

  • They share 13 benchmarks with published results for both. GLM-4.5V scores higher in 4 categories and GLM-4.7-Flash in 4 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-4.5V leads 27.4 to 20.9.
  • GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.60 / $1.80 for GLM-4.5V.
  • GLM-4.7-Flash accepts more context: 200K tokens versus 64K.

Side by side

GLM-4.5V and GLM-4.7-Flash specifications
GLM-4.5VGLM-4.7-Flash
ProviderZ.ai (Zhipu)Z.ai (Zhipu)
Noometry Index39.838.8
Released2025-08-112026-01-19
WeightsOpenOpen
Context window64K200K
Max output16K131K
Input $ / M tokens$0.60$0.06
Output $ / M tokens$1.80$0.40
Results tracked1521

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Category by category

Coding GLM-4.7-Flash leads

GLM-4.5V: 39.5 (#155), GLM-4.7-Flash: 40.6 (#135)

Coding benchmarks
BenchmarkGLM-4.5VGLM-4.7-Flash
LMArena Coding13471383

Reasoning GLM-4.5V leads

GLM-4.5V: 27.4 (#119), GLM-4.7-Flash: 20.9 (#229)

Reasoning benchmarks
BenchmarkGLM-4.5VGLM-4.7-Flash
LMArena Hard Prompts13341356
Kagi LLM Benchmark59.8%—
Chess Puzzles—0%

Math GLM-4.5V leads

GLM-4.5V: 37.4 (#159), GLM-4.7-Flash: 36.1 (#173)

Math benchmarks
BenchmarkGLM-4.5VGLM-4.7-Flash
LMArena Math13541355
OTIS Mock AIME 2024-2025—58.3%

Knowledge GLM-4.5V leads

GLM-4.5V: 37.5 (#156), GLM-4.7-Flash: 35.5 (#184)

Knowledge benchmarks
BenchmarkGLM-4.5VGLM-4.7-Flash
LMArena Expert13531357
GPQA Diamond—60.5%
Vectara Hallucination Rate—9.3%

Multimodal Not comparable

GLM-4.5V: 34.3 (#92), GLM-4.7-Flash: —

Multimodal benchmarks
BenchmarkGLM-4.5VGLM-4.7-Flash
LMArena Vision1154—

Multilingual GLM-4.7-Flash leads

GLM-4.5V: 44.6 (#177), GLM-4.7-Flash: 46.5 (#158)

Multilingual benchmarks
BenchmarkGLM-4.5VGLM-4.7-Flash
LMArena Non-English13031330
LMArena Chinese13371403
LMArena Russian12981332
LMArena Spanish13361350
LMArena French—1332
LMArena German—1337
LMArena Korean—1283

Instruction Following Too close to call

GLM-4.5V: 69.2 (#175), GLM-4.7-Flash: 70.1 (#167)

Instruction Following benchmarks
BenchmarkGLM-4.5VGLM-4.7-Flash
LMArena Instruction Following13111327

Long Context GLM-4.7-Flash leads

GLM-4.5V: 39.6 (#171), GLM-4.7-Flash: 40.9 (#148)

Long Context benchmarks
BenchmarkGLM-4.5VGLM-4.7-Flash
LMArena Longer Query13041345

Writing & Preference GLM-4.5V leads

GLM-4.5V: 52.5 (#170), GLM-4.7-Flash: 47.4 (#210)

Writing & Preference benchmarks
BenchmarkGLM-4.5VGLM-4.7-Flash
LMArena Text13331351
LMArena Creative Writing12951297
LMArena Multi-Turn13321342
EQ-Bench Creative Writing—1125

Frequently asked questions

Is GLM-4.5V better than GLM-4.7-Flash?

GLM-4.5V and GLM-4.7-Flash score almost the same on the Noometry Index (39.8 vs 38.8), so choose on price, context window or the category you care about most.

Which is cheaper, GLM-4.5V or GLM-4.7-Flash?

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; GLM-4.5V lists at $0.60 and $1.80.

Is GLM-4.5V or GLM-4.7-Flash better for coding?

GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 39.5 in the Noometry coding category.

Which has the bigger context window?

GLM-4.7-Flash does, with 200K tokens against 64K.

How many benchmarks do GLM-4.5V and GLM-4.7-Flash share?

13 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and GLM-4.7-Flash has 21.

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