Model comparison

GLM-5.2 vs Qwen1.5-72B

GLM-5.2 is the stronger model overall, scoring 51.1 to 30.8 on the Noometry Index.

Last verified . 18 shared benchmarks.

GLM-5.2 Z.ai (Zhipu)

51.1

Rank #44 Confirmed

Qwen1.5-72B Alibaba (Qwen)

30.8

Rank #285 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GLM-5.2 scores higher in 8 categories and Qwen1.5-72B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-5.2 leads 57.1 to 11.5.
  • The biggest single-benchmark swing is GPQA Diamond: 91.9% for GLM-5.2 and 28.8% for Qwen1.5-72B.

Side by side

GLM-5.2 and Qwen1.5-72B specifications
GLM-5.2Qwen1.5-72B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index51.130.8
Released2026-06-132024-02-04
WeightsOpenOpen
Context window1M—
Max output131K—
Input $ / M tokens$1.40—
Output $ / M tokens$4.40—
Results tracked5122

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Category by category

Coding GLM-5.2 leads

GLM-5.2: 51.3 (#41), Qwen1.5-72B: 31.9 (#277)

Coding benchmarks
BenchmarkGLM-5.2Qwen1.5-72B
LMArena Coding14851165
SWE-bench Verified78.7%—
DeepSWE43.8%—
FrontierCode24.5%—
LMArena WebDev1603—
SciCode50.5%—
WeirdML70.1%—
BigCodeBench Instruct—33.2%
BigCodeBench Complete—40.3%
ALE-Bench1,047—
HumanEval+—59.1%
MBPP+—61.6%

Agentic & Tool Use Not comparable

GLM-5.2: 32.4 (#63), Qwen1.5-72B: —

Agentic & Tool Use benchmarks
BenchmarkGLM-5.2Qwen1.5-72B
APEX-Agents45.2%—
τ²-bench Banking37.1%—
PostTrainBench31.7%—
GBAEval0%—
Vending-Bench 28,314—

Reasoning GLM-5.2 leads

GLM-5.2: 42.3 (#52), Qwen1.5-72B: 22.2 (#203)

Reasoning benchmarks
BenchmarkGLM-5.2Qwen1.5-72B
LMArena Hard Prompts14801148
ARC-AGI-222.8%—
SimpleBench58.8%—
Kagi LLM Benchmark62.6%—
NYT Connections (extended)74.3%—
ARC-AGI-177%—
CritPt20.9%—
Chess Puzzles21%—
EBR-Bench9.5%—
Mystery Game Puzzles19%—
DTBench93.6%—
LMCA45.8%—
Surface Evolver Bench55.6%—
Epoch Capabilities Index151.78—

Math GLM-5.2 leads

GLM-5.2: 55.7 (#43), Qwen1.5-72B: 33.2 (#205)

Math benchmarks
BenchmarkGLM-5.2Qwen1.5-72B
LMArena Math14821164
FrontierMath (Tiers 1-3)59.2%—
FrontierMath Tier 429.3%—
MathArena Final-Answer Competitions67.6%—
OTIS Mock AIME 2024-202586.4%—
ProofBench35%—

Knowledge GLM-5.2 leads

GLM-5.2: 57.1 (#40), Qwen1.5-72B: 11.5 (#300)

Knowledge benchmarks
BenchmarkGLM-5.2Qwen1.5-72B
GPQA Diamond91.9%28.8%
LMArena Expert14861136
SimpleQA Verified34.2%—

Multilingual GLM-5.2 leads

GLM-5.2: 55.8 (#26), Qwen1.5-72B: 33.2 (#253)

Multilingual benchmarks
BenchmarkGLM-5.2Qwen1.5-72B
LMArena Non-English14591135
LMArena Chinese15191186
LMArena French14791159
LMArena German14681084
LMArena Japanese14511061
LMArena Korean14451050
LMArena Russian14661104
LMArena Spanish14771110

Instruction Following GLM-5.2 leads

GLM-5.2: 76.9 (#34), Qwen1.5-72B: 59.3 (#256)

Instruction Following benchmarks
BenchmarkGLM-5.2Qwen1.5-72B
LMArena Instruction Following14651141

Long Context GLM-5.2 leads

GLM-5.2: 45.3 (#43), Qwen1.5-72B: 35.1 (#243)

Long Context benchmarks
BenchmarkGLM-5.2Qwen1.5-72B
LMArena Longer Query14791157

Writing & Preference GLM-5.2 leads

GLM-5.2: 70.4 (#21), Qwen1.5-72B: 37.3 (#258)

Writing & Preference benchmarks
BenchmarkGLM-5.2Qwen1.5-72B
LMArena Text14701166
LMArena Creative Writing14621137
LMArena Multi-Turn14691160
EQ-Bench Creative Writing1757—
EQ-Bench 41222—

Frequently asked questions

Is GLM-5.2 better than Qwen1.5-72B?

GLM-5.2 is the stronger model overall, scoring 51.1 to 30.8 on the Noometry Index.

Is GLM-5.2 or Qwen1.5-72B better for coding?

GLM-5.2 scores higher on coding benchmarks: 51.3 versus 31.9 in the Noometry coding category.

How many benchmarks do GLM-5.2 and Qwen1.5-72B share?

18 benchmarks have published results for both models. GLM-5.2 has 51 scored results on Noometry and Qwen1.5-72B has 22.

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