Noometry

Model comparison

GLM-4.5V vs Qwen3.7 Max

Qwen3.7 Max is the stronger model overall, scoring 51.5 to 39.8 on the Noometry Index. GLM-4.5V costs 4.2× less per token, which makes it the better buy when Qwen3.7 Max's lead doesn't matter for your workload.

Last verified . 12 shared benchmarks.

GLM-4.5V Z.ai (Zhipu)

39.8

Rank #158 Confirmed

Qwen3.7 Max Alibaba (Qwen)

51.5

Rank #42 Confirmed

Summary

  • They share 12 benchmarks with published results for both. GLM-4.5V scores higher in 0 categories and Qwen3.7 Max in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where Qwen3.7 Max leads 62.4 to 37.4.
  • GLM-4.5V is cheaper at $0.60 / $1.80 per million input/output tokens, against $2.50 / $7.50 for Qwen3.7 Max.
  • Qwen3.7 Max accepts more context: 1M tokens versus 64K.
  • GLM-4.5V has downloadable open weights; the other is API-only.

Side by side

GLM-4.5VQwen3.7 Max
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index39.851.5
Released2025-08-112026-05-19
WeightsOpenProprietary
Context window64K1M
Max output16K131K
Input $ / M tokens$0.60$2.50
Output $ / M tokens$1.80$7.50
Results tracked1533

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Category by category

Coding Qwen3.7 Max leads

GLM-4.5V: 39.5 (#155), Qwen3.7 Max: 50.4 (#45)

BenchmarkGLM-4.5VQwen3.7 Max
LMArena Coding13471498
SWE-bench Verified—77.3%
LMArena WebDev—1515
SciCode—48.8%
ALE-Bench—1,189

Agentic & Tool Use Not comparable

GLM-4.5V: —, Qwen3.7 Max: 22.1 (#135)

BenchmarkGLM-4.5VQwen3.7 Max
GBAEval—0.4%

Reasoning Qwen3.7 Max leads

GLM-4.5V: 27.4 (#119), Qwen3.7 Max: 49.2 (#38)

BenchmarkGLM-4.5VQwen3.7 Max
LMArena Hard Prompts13341483
SimpleBench—70.4%
Kagi LLM Benchmark59.8%—
NYT Connections (extended)—85.1%
CritPt—13.4%
Chess Puzzles—19%
EBR-Bench—9.5%
Mystery Game Puzzles—32%
DTBench—92.3%
LMCA—44%
Epoch Capabilities Index—153.68

Math Qwen3.7 Max leads

GLM-4.5V: 37.4 (#159), Qwen3.7 Max: 62.4 (#32)

BenchmarkGLM-4.5VQwen3.7 Max
LMArena Math13541490
FrontierMath (Tiers 1-3)—64.6%
FrontierMath Tier 4—34.1%
OTIS Mock AIME 2024-2025—95.6%
ProofBench—26%

Knowledge Qwen3.7 Max leads

GLM-4.5V: 37.5 (#156), Qwen3.7 Max: 61.6 (#28)

BenchmarkGLM-4.5VQwen3.7 Max
LMArena Expert13531488
GPQA Diamond—90.9%
SimpleQA Verified—55.8%

Multimodal Not comparable

GLM-4.5V: 34.3 (#92), Qwen3.7 Max: —

BenchmarkGLM-4.5VQwen3.7 Max
LMArena Vision1154—

Multilingual Qwen3.7 Max leads

GLM-4.5V: 44.6 (#177), Qwen3.7 Max: 56.9 (#15)

BenchmarkGLM-4.5VQwen3.7 Max
LMArena Non-English13031474
LMArena Chinese13371530
LMArena Russian12981484
LMArena Spanish1336—

Instruction Following Qwen3.7 Max leads

GLM-4.5V: 69.2 (#175), Qwen3.7 Max: 76.7 (#38)

BenchmarkGLM-4.5VQwen3.7 Max
LMArena Instruction Following13111460

Long Context Qwen3.7 Max leads

GLM-4.5V: 39.6 (#171), Qwen3.7 Max: 45.4 (#40)

BenchmarkGLM-4.5VQwen3.7 Max
LMArena Longer Query13041482

Writing & Preference Qwen3.7 Max leads

GLM-4.5V: 52.5 (#170), Qwen3.7 Max: 65.0 (#54)

BenchmarkGLM-4.5VQwen3.7 Max
LMArena Text13331476
LMArena Creative Writing12951449
LMArena Multi-Turn13321481
EQ-Bench 4—1110

Frequently asked questions

Is GLM-4.5V better than Qwen3.7 Max?

Qwen3.7 Max is the stronger model overall, scoring 51.5 to 39.8 on the Noometry Index. GLM-4.5V costs 4.2× less per token, which makes it the better buy when Qwen3.7 Max's lead doesn't matter for your workload.

Which is cheaper, GLM-4.5V or Qwen3.7 Max?

GLM-4.5V is cheaper. It lists at $0.60 per million input tokens and $1.80 per million output tokens; Qwen3.7 Max lists at $2.50 and $7.50.

Is GLM-4.5V or Qwen3.7 Max better for coding?

Qwen3.7 Max scores higher on coding benchmarks: 50.4 versus 39.5 in the Noometry coding category.

Which has the bigger context window?

Qwen3.7 Max does, with 1M tokens against 64K.

How many benchmarks do GLM-4.5V and Qwen3.7 Max share?

12 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and Qwen3.7 Max has 33.

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