Model comparison

GLM-5.2 vs Qwen-14B

GLM-5.2 is the stronger model overall, scoring 51.1 to 31.4 on the Noometry Index.

Last verified . 11 shared benchmarks.

GLM-5.2 Z.ai (Zhipu)

51.1

Rank #44 Confirmed

Qwen-14B Alibaba (Qwen)

31.4

Rank #275 Confirmed

Summary

  • They share 11 benchmarks with published results for both. GLM-5.2 scores higher in 7 categories and Qwen-14B in 0 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-5.2 leads 70.4 to 27.6.

Side by side

GLM-5.2 and Qwen-14B specifications
GLM-5.2Qwen-14B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index51.131.4
Released2026-06-132023-09-24
WeightsOpenOpen
Context window1M—
Max output131K—
Input $ / M tokens$1.40—
Output $ / M tokens$4.40—
Results tracked5118

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Category by category

Coding GLM-5.2 leads

GLM-5.2: 51.3 (#41), Qwen-14B: 31.2 (#288)

Coding benchmarks
BenchmarkGLM-5.2Qwen-14B
LMArena Coding14851071
SWE-bench Verified78.7%—
DeepSWE43.8%—
FrontierCode24.5%—
LMArena WebDev1603—
SciCode50.5%—
WeirdML70.1%—
ALE-Bench1,047—

Agentic & Tool Use Not comparable

GLM-5.2: 32.4 (#63), Qwen-14B: —

Agentic & Tool Use benchmarks
BenchmarkGLM-5.2Qwen-14B
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), Qwen-14B: 19.6 (#257)

Reasoning benchmarks
BenchmarkGLM-5.2Qwen-14B
LMArena Hard Prompts14801027
Epoch Capabilities Index151.78113.03
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%—
BIG-Bench Hard—55%
LAMBADA—71.1%
PIQA—79.9%

Math GLM-5.2 leads

GLM-5.2: 55.7 (#43), Qwen-14B: 31.2 (#227)

Math benchmarks
BenchmarkGLM-5.2Qwen-14B
LMArena Math14821068
FrontierMath (Tiers 1-3)59.2%—
FrontierMath Tier 429.3%—
MathArena Final-Answer Competitions67.6%—
OTIS Mock AIME 2024-202586.4%—
ProofBench35%—
GSM8K—61.3%

Knowledge Not comparable

GLM-5.2: 57.1 (#40), Qwen-14B: —

Knowledge benchmarks
BenchmarkGLM-5.2Qwen-14B
GPQA Diamond91.9%—
SimpleQA Verified34.2%—
LMArena Expert1486—
ARC (AI2) Challenge—84.4%
BoolQ—86.2%
MMLU—66.3%

Multilingual GLM-5.2 leads

GLM-5.2: 55.8 (#26), Qwen-14B: 27.5 (#275)

Multilingual benchmarks
BenchmarkGLM-5.2Qwen-14B
LMArena Non-English14591041
LMArena Chinese15191077
LMArena French1479—
LMArena German1468—
LMArena Japanese1451—
LMArena Korean1445—
LMArena Russian1466—
LMArena Spanish1477—

Instruction Following GLM-5.2 leads

GLM-5.2: 76.9 (#34), Qwen-14B: 52.4 (#289)

Instruction Following benchmarks
BenchmarkGLM-5.2Qwen-14B
LMArena Instruction Following14651031

Long Context GLM-5.2 leads

GLM-5.2: 45.3 (#43), Qwen-14B: 31.3 (#280)

Long Context benchmarks
BenchmarkGLM-5.2Qwen-14B
LMArena Longer Query14791028

Writing & Preference GLM-5.2 leads

GLM-5.2: 70.4 (#21), Qwen-14B: 27.6 (#299)

Writing & Preference benchmarks
BenchmarkGLM-5.2Qwen-14B
LMArena Text14701051
LMArena Creative Writing14621028
LMArena Multi-Turn14691022
EQ-Bench Creative Writing1757—
EQ-Bench 41222—

Frequently asked questions

Is GLM-5.2 better than Qwen-14B?

GLM-5.2 is the stronger model overall, scoring 51.1 to 31.4 on the Noometry Index.

Is GLM-5.2 or Qwen-14B better for coding?

GLM-5.2 scores higher on coding benchmarks: 51.3 versus 31.2 in the Noometry coding category.

How many benchmarks do GLM-5.2 and Qwen-14B share?

11 benchmarks have published results for both models. GLM-5.2 has 51 scored results on Noometry and Qwen-14B has 18.

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