Noometry

Model comparison

GLM-4.7 vs Qwen3-VL 235B-A22B

Qwen3-VL 235B-A22B is the stronger model overall, scoring 43.2 to 42.0 on the Noometry Index.

Last verified . 17 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

42.0

Rank #124 Confirmed

Qwen3-VL 235B-A22B Alibaba (Qwen)

43.2

Rank #95 Confirmed

Summary

  • They share 17 benchmarks with published results for both. GLM-4.7 scores higher in 5 categories and Qwen3-VL 235B-A22B in 3 categories; 3 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.7 leads 47.0 to 40.3.
  • GLM-4.7 is cheaper at $0.60 / $2.20 per million input/output tokens, against $0.70 / $2.80 for Qwen3-VL 235B-A22B.
  • GLM-4.7 accepts more context: 205K tokens versus 131K.

Side by side

GLM-4.7Qwen3-VL 235B-A22B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index42.043.2
Released2025-12-222025-04
WeightsOpenOpen
Context window205K131K
Max output131K33K
Input $ / M tokens$0.60$0.70
Output $ / M tokens$2.20$2.80
Results tracked3618

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Category by category

Coding GLM-4.7 leads

GLM-4.7: 44.0 (#79), Qwen3-VL 235B-A22B: 42.4 (#100)

BenchmarkGLM-4.7Qwen3-VL 235B-A22B
LMArena Coding14541439
LMArena WebDev1435—
SciCode45.1%—
ALE-Bench399.48—

Agentic & Tool Use Not comparable

GLM-4.7: 26.5 (#103), Qwen3-VL 235B-A22B: —

BenchmarkGLM-4.7Qwen3-VL 235B-A22B
Terminal-Bench33.4%—
Vending-Bench 22,377—

Reasoning Qwen3-VL 235B-A22B leads

GLM-4.7: 24.3 (#164), Qwen3-VL 235B-A22B: 29.3 (#92)

BenchmarkGLM-4.7Qwen3-VL 235B-A22B
LMArena Hard Prompts14431428
SimpleBench47.7%—
CritPt1.7%—
Chess Puzzles6%—
Epoch Capabilities Index143.51—

Math Too close to call

GLM-4.7: 38.6 (#135), Qwen3-VL 235B-A22B: 39.0 (#118)

BenchmarkGLM-4.7Qwen3-VL 235B-A22B
LMArena Math14231426
OTIS Mock AIME 2024-202583.3%—
ProofBench6%—
FrontierMath (Feb 2025 set)2.4%—
FrontierMath Tier 4 (v1)0%—

Knowledge GLM-4.7 leads

GLM-4.7: 47.0 (#80), Qwen3-VL 235B-A22B: 40.3 (#121)

BenchmarkGLM-4.7Qwen3-VL 235B-A22B
LMArena Expert14241442
GPQA Diamond83.3%—
SimpleQA Verified32.2%—
Vectara Hallucination Rate11.7%—

Multimodal Not comparable

GLM-4.7: —, Qwen3-VL 235B-A22B: 39.8 (#55)

BenchmarkGLM-4.7Qwen3-VL 235B-A22B
LMArena Vision—1247

Multilingual Too close to call

GLM-4.7: 52.8 (#79), Qwen3-VL 235B-A22B: 51.9 (#97)

BenchmarkGLM-4.7Qwen3-VL 235B-A22B
LMArena Non-English14171405
LMArena Chinese14951463
LMArena French14321452
LMArena German14241424
LMArena Japanese14391385
LMArena Korean13991394
LMArena Russian14231408
LMArena Spanish14341428

Instruction Following Too close to call

GLM-4.7: 74.4 (#95), Qwen3-VL 235B-A22B: 74.2 (#101)

BenchmarkGLM-4.7Qwen3-VL 235B-A22B
LMArena Instruction Following14111406

Long Context Too close to call

GLM-4.7: 42.8 (#116), Qwen3-VL 235B-A22B: 43.4 (#98)

BenchmarkGLM-4.7Qwen3-VL 235B-A22B
LMArena Longer Query14321420
CL-bench15.9%—
CL-bench Life10.9%—

Writing & Preference Too close to call

GLM-4.7: 60.9 (#93), Qwen3-VL 235B-A22B: 60.2 (#99)

BenchmarkGLM-4.7Qwen3-VL 235B-A22B
LMArena Text14351420
LMArena Creative Writing14011366
LMArena Multi-Turn14461428
EQ-Bench Creative Writing1413—

Frequently asked questions

Is GLM-4.7 better than Qwen3-VL 235B-A22B?

Qwen3-VL 235B-A22B is the stronger model overall, scoring 43.2 to 42.0 on the Noometry Index.

Which is cheaper, GLM-4.7 or Qwen3-VL 235B-A22B?

GLM-4.7 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Qwen3-VL 235B-A22B lists at $0.70 and $2.80.

Is GLM-4.7 or Qwen3-VL 235B-A22B better for coding?

GLM-4.7 scores higher on coding benchmarks: 44.0 versus 42.4 in the Noometry coding category.

Which has the bigger context window?

GLM-4.7 does, with 205K tokens against 131K.

How many benchmarks do GLM-4.7 and Qwen3-VL 235B-A22B share?

17 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Qwen3-VL 235B-A22B has 18.

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