Noometry

Model comparison

GLM-4.7-Flash vs Qwen2.5-VL 72B Instruct

GLM-4.7-Flash is the stronger model overall, scoring 38.4 to 29.4 on the Noometry Index.

Last verified . 0 shared benchmarks.

GLM-4.7-Flash Z.ai (Zhipu)

38.4

Rank #175 Confirmed

Qwen2.5-VL 72B Instruct Alibaba (Qwen)

29.4

Rank #298 Confirmed

Summary

  • GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $2.80 / $8.40 for Qwen2.5-VL 72B Instruct.
  • GLM-4.7-Flash accepts more context: 200K tokens versus 131K.

Side by side

GLM-4.7-FlashQwen2.5-VL 72B Instruct
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index38.429.4
Released2026-01-192024-09
WeightsOpenOpen
Context window200K131K
Max output131K8K
Input $ / M tokens$0.06$2.80
Output $ / M tokens$0.40$8.40
Results tracked216

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Category by category

Coding Not comparable

GLM-4.7-Flash: 40.0 (#133), Qwen2.5-VL 72B Instruct: —

BenchmarkGLM-4.7-FlashQwen2.5-VL 72B Instruct
LMArena Coding1383—

Agentic & Tool Use Not comparable

GLM-4.7-Flash: —, Qwen2.5-VL 72B Instruct: 18.4 (#136)

BenchmarkGLM-4.7-FlashQwen2.5-VL 72B Instruct
OSWorld—5%

Reasoning Too close to call

GLM-4.7-Flash: 20.2 (#224), Qwen2.5-VL 72B Instruct: 20.0 (#228)

BenchmarkGLM-4.7-FlashQwen2.5-VL 72B Instruct
Kagi LLM Benchmark—36%
Chess Puzzles0%—
LMArena Hard Prompts1356—

Math Not comparable

GLM-4.7-Flash: 34.4 (#159), Qwen2.5-VL 72B Instruct: —

BenchmarkGLM-4.7-FlashQwen2.5-VL 72B Instruct
OTIS Mock AIME 2024-202558.3%—
LMArena Math1354—

Knowledge Not comparable

GLM-4.7-Flash: 35.4 (#177), Qwen2.5-VL 72B Instruct: —

BenchmarkGLM-4.7-FlashQwen2.5-VL 72B Instruct
GPQA Diamond60.5%—
Vectara Hallucination Rate9.3%—
LMArena Expert1357—

Multimodal Not comparable

GLM-4.7-Flash: —, Qwen2.5-VL 72B Instruct: 32.9 (#92)

BenchmarkGLM-4.7-FlashQwen2.5-VL 72B Instruct
LMArena Vision—1107
Video-MME—73.5%
GeoBench—62%
SpatialViz-Bench—33.3%

Multilingual Not comparable

GLM-4.7-Flash: 46.8 (#152), Qwen2.5-VL 72B Instruct: —

BenchmarkGLM-4.7-FlashQwen2.5-VL 72B Instruct
LMArena Non-English1331—
LMArena Chinese1403—
LMArena French1332—
LMArena German1336—
LMArena Korean1284—
LMArena Russian1333—
LMArena Spanish1351—

Instruction Following Not comparable

GLM-4.7-Flash: 70.3 (#162), Qwen2.5-VL 72B Instruct: —

BenchmarkGLM-4.7-FlashQwen2.5-VL 72B Instruct
LMArena Instruction Following1327—

Long Context Not comparable

GLM-4.7-Flash: 40.9 (#143), Qwen2.5-VL 72B Instruct: —

BenchmarkGLM-4.7-FlashQwen2.5-VL 72B Instruct
LMArena Longer Query1345—

Writing & Preference Not comparable

GLM-4.7-Flash: 47.7 (#206), Qwen2.5-VL 72B Instruct: —

BenchmarkGLM-4.7-FlashQwen2.5-VL 72B Instruct
LMArena Text1351—
LMArena Creative Writing1297—
EQ-Bench Creative Writing1125—
LMArena Multi-Turn1342—

Frequently asked questions

Is GLM-4.7-Flash better than Qwen2.5-VL 72B Instruct?

GLM-4.7-Flash is the stronger model overall, scoring 38.4 to 29.4 on the Noometry Index.

Which is cheaper, GLM-4.7-Flash or Qwen2.5-VL 72B Instruct?

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; Qwen2.5-VL 72B Instruct lists at $2.80 and $8.40.

Which has the bigger context window?

GLM-4.7-Flash does, with 200K tokens against 131K.

How many benchmarks do GLM-4.7-Flash and Qwen2.5-VL 72B Instruct share?

0 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Qwen2.5-VL 72B Instruct has 6.

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