Model comparison

GLM-5.2 vs Qwen2-72B

GLM-5.2 is the stronger model overall, scoring 51.1 to 30.0 on the Noometry Index.

Last verified . 20 shared benchmarks.

GLM-5.2 Z.ai (Zhipu)

51.1

Rank #44 Confirmed

Qwen2-72B Alibaba (Qwen)

30.0

Rank #300 Confirmed

Summary

  • They share 20 benchmarks with published results for both. GLM-5.2 scores higher in 9 categories and Qwen2-72B in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-5.2 leads 57.1 to 21.2.
  • The biggest single-benchmark swing is WeirdML: 70.1% for GLM-5.2 and 11.3% for Qwen2-72B.

Side by side

GLM-5.2 and Qwen2-72B specifications
GLM-5.2Qwen2-72B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index51.130.0
Released2026-06-132024-06-07
WeightsOpenOpen
Context window1M—
Max output131K—
Input $ / M tokens$1.40—
Output $ / M tokens$4.40—
Results tracked5126

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Category by category

Coding GLM-5.2 leads

GLM-5.2: 51.3 (#41), Qwen2-72B: 29.1 (#310)

Coding benchmarks
BenchmarkGLM-5.2Qwen2-72B
WeirdML70.1%11.3%
LMArena Coding14851196
SWE-bench Verified78.7%—
DeepSWE43.8%—
FrontierCode24.5%—
LMArena WebDev1603—
SciCode50.5%—
BigCodeBench Instruct—38.5%
BigCodeBench Complete—54%
ALE-Bench1,047—

Agentic & Tool Use GLM-5.2 leads

GLM-5.2: 32.4 (#63), Qwen2-72B: 17.0 (#146)

Agentic & Tool Use benchmarks
BenchmarkGLM-5.2Qwen2-72B
APEX-Agents45.2%—
TheAgentCompany—1.1%
τ²-bench Banking37.1%—
PostTrainBench31.7%—
GBAEval0%—
METR Time Horizons—29.9%
Vending-Bench 28,314—

Reasoning GLM-5.2 leads

GLM-5.2: 42.3 (#52), Qwen2-72B: 23.2 (#181)

Reasoning benchmarks
BenchmarkGLM-5.2Qwen2-72B
LMArena Hard Prompts14801191
Epoch Capabilities Index151.78125.28
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%—

Math GLM-5.2 leads

GLM-5.2: 55.7 (#43), Qwen2-72B: 30.2 (#236)

Math benchmarks
BenchmarkGLM-5.2Qwen2-72B
LMArena Math14821235
FrontierMath (Tiers 1-3)59.2%—
FrontierMath Tier 429.3%—
MathArena Final-Answer Competitions67.6%—
OTIS Mock AIME 2024-202586.4%—
ProofBench35%—
MATH Level 5—39.1%

Knowledge GLM-5.2 leads

GLM-5.2: 57.1 (#40), Qwen2-72B: 21.2 (#275)

Knowledge benchmarks
BenchmarkGLM-5.2Qwen2-72B
GPQA Diamond91.9%40.8%
LMArena Expert14861171
SimpleQA Verified34.2%—
MMLU—82.4%

Multilingual GLM-5.2 leads

GLM-5.2: 55.8 (#26), Qwen2-72B: 35.9 (#244)

Multilingual benchmarks
BenchmarkGLM-5.2Qwen2-72B
LMArena Non-English14591176
LMArena Chinese15191240
LMArena French14791170
LMArena German14681151
LMArena Japanese14511111
LMArena Korean14451083
LMArena Russian14661169
LMArena Spanish14771169

Instruction Following GLM-5.2 leads

GLM-5.2: 76.9 (#34), Qwen2-72B: 61.7 (#241)

Instruction Following benchmarks
BenchmarkGLM-5.2Qwen2-72B
LMArena Instruction Following14651181

Long Context GLM-5.2 leads

GLM-5.2: 45.3 (#43), Qwen2-72B: 36.1 (#235)

Long Context benchmarks
BenchmarkGLM-5.2Qwen2-72B
LMArena Longer Query14791192

Writing & Preference GLM-5.2 leads

GLM-5.2: 70.4 (#21), Qwen2-72B: 40.8 (#241)

Writing & Preference benchmarks
BenchmarkGLM-5.2Qwen2-72B
LMArena Text14701203
LMArena Creative Writing14621181
LMArena Multi-Turn14691196
EQ-Bench Creative Writing1757—
EQ-Bench 41222—

Frequently asked questions

Is GLM-5.2 better than Qwen2-72B?

GLM-5.2 is the stronger model overall, scoring 51.1 to 30.0 on the Noometry Index.

Is GLM-5.2 or Qwen2-72B better for coding?

GLM-5.2 scores higher on coding benchmarks: 51.3 versus 29.1 in the Noometry coding category.

How many benchmarks do GLM-5.2 and Qwen2-72B share?

20 benchmarks have published results for both models. GLM-5.2 has 51 scored results on Noometry and Qwen2-72B has 26.

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