Model comparison

GLM-5.2 vs Qwen2.5-Coder (1.5B)

GLM-5.2 has enough public results to be ranked (#44); Qwen2.5-Coder (1.5B) does not yet, so treat this comparison as directional.

Last verified . 1 shared benchmarks.

GLM-5.2 Z.ai (Zhipu)

51.1

Rank #44 Confirmed

Summary

  • They share 1 benchmark with published results for both.

Side by side

GLM-5.2 and Qwen2.5-Coder (1.5B) specifications
GLM-5.2Qwen2.5-Coder (1.5B)
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index51.1—
Released2026-06-132024-09-18
WeightsOpenOpen
Context window1M—
Max output131K—
Input $ / M tokens$1.40—
Output $ / M tokens$4.40—
Results tracked516

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Category by category

Coding Not comparable

GLM-5.2: 51.3 (#41), Qwen2.5-Coder (1.5B): —

Coding benchmarks
BenchmarkGLM-5.2Qwen2.5-Coder (1.5B)
SWE-bench Verified78.7%—
DeepSWE43.8%—
FrontierCode24.5%—
LMArena WebDev1603—
SciCode50.5%—
WeirdML70.1%—
LMArena Coding1485—
ALE-Bench1,047—

Agentic & Tool Use Not comparable

GLM-5.2: 32.4 (#63), Qwen2.5-Coder (1.5B): —

Agentic & Tool Use benchmarks
BenchmarkGLM-5.2Qwen2.5-Coder (1.5B)
APEX-Agents45.2%—
τ²-bench Banking37.1%—
PostTrainBench31.7%—
GBAEval0%—
Vending-Bench 28,314—

Reasoning Not comparable

GLM-5.2: 42.3 (#52), Qwen2.5-Coder (1.5B): —

Reasoning benchmarks
BenchmarkGLM-5.2Qwen2.5-Coder (1.5B)
Epoch Capabilities Index151.78113.14
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%—
LMArena Hard Prompts1480—
Mystery Game Puzzles19%—
DTBench93.6%—
LMCA45.8%—
Surface Evolver Bench55.6%—
HellaSwag—76.8%
WinoGrande—72.9%

Math Not comparable

GLM-5.2: 55.7 (#43), Qwen2.5-Coder (1.5B): —

Math benchmarks
BenchmarkGLM-5.2Qwen2.5-Coder (1.5B)
FrontierMath (Tiers 1-3)59.2%—
FrontierMath Tier 429.3%—
MathArena Final-Answer Competitions67.6%—
OTIS Mock AIME 2024-202586.4%—
ProofBench35%—
LMArena Math1482—
GSM8K—86.7%

Knowledge Not comparable

GLM-5.2: 57.1 (#40), Qwen2.5-Coder (1.5B): —

Knowledge benchmarks
BenchmarkGLM-5.2Qwen2.5-Coder (1.5B)
GPQA Diamond91.9%—
SimpleQA Verified34.2%—
LMArena Expert1486—
ARC (AI2) Challenge—60.9%
MMLU—68%

Multilingual Not comparable

GLM-5.2: 55.8 (#26), Qwen2.5-Coder (1.5B): —

Multilingual benchmarks
BenchmarkGLM-5.2Qwen2.5-Coder (1.5B)
LMArena Non-English1459—
LMArena Chinese1519—
LMArena French1479—
LMArena German1468—
LMArena Japanese1451—
LMArena Korean1445—
LMArena Russian1466—
LMArena Spanish1477—

Instruction Following Not comparable

GLM-5.2: 76.9 (#34), Qwen2.5-Coder (1.5B): —

Instruction Following benchmarks
BenchmarkGLM-5.2Qwen2.5-Coder (1.5B)
LMArena Instruction Following1465—

Long Context Not comparable

GLM-5.2: 45.3 (#43), Qwen2.5-Coder (1.5B): —

Long Context benchmarks
BenchmarkGLM-5.2Qwen2.5-Coder (1.5B)
LMArena Longer Query1479—

Writing & Preference Not comparable

GLM-5.2: 70.4 (#21), Qwen2.5-Coder (1.5B): —

Writing & Preference benchmarks
BenchmarkGLM-5.2Qwen2.5-Coder (1.5B)
LMArena Text1470—
LMArena Creative Writing1462—
EQ-Bench Creative Writing1757—
EQ-Bench 41222—
LMArena Multi-Turn1469—

Frequently asked questions

Is GLM-5.2 better than Qwen2.5-Coder (1.5B)?

GLM-5.2 has enough public results to be ranked (#44); Qwen2.5-Coder (1.5B) does not yet, so treat this comparison as directional.

How many benchmarks do GLM-5.2 and Qwen2.5-Coder (1.5B) share?

1 benchmark has published results for both models. GLM-5.2 has 51 scored results on Noometry and Qwen2.5-Coder (1.5B) has 6.

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