Model comparison

GLM-5.2 vs Hunyuan Large Vision

GLM-5.2 is the stronger model overall, scoring 51.1 to 37.6 on the Noometry Index.

Last verified . 12 shared benchmarks.

GLM-5.2 Z.ai (Zhipu)

51.1

Rank #44 Confirmed

Hunyuan Large Vision Tencent

37.6

Rank #202 Confirmed

Summary

  • They share 12 benchmarks with published results for both. GLM-5.2 scores higher in 8 categories and Hunyuan Large Vision in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-5.2 leads 70.4 to 46.5.
  • GLM-5.2 has downloadable open weights; the other is API-only.

Side by side

GLM-5.2 and Hunyuan Large Vision specifications
GLM-5.2Hunyuan Large Vision
ProviderZ.ai (Zhipu)Tencent
Noometry Index51.137.6
Released2026-06-13—
WeightsOpenProprietary
Context window1M—
Max output131K—
Input $ / M tokens$1.40—
Output $ / M tokens$4.40—
Results tracked5113

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Category by category

Coding GLM-5.2 leads

GLM-5.2: 51.3 (#41), Hunyuan Large Vision: 38.3 (#180)

Coding benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
LMArena Coding14851308
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), Hunyuan Large Vision: —

Agentic & Tool Use benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
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), Hunyuan Large Vision: 24.8 (#158)

Reasoning benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
LMArena Hard Prompts14801257
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), Hunyuan Large Vision: 35.5 (#183)

Math benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
LMArena Math14821268
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), Hunyuan Large Vision: 34.4 (#196)

Knowledge benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
LMArena Expert14861252
GPQA Diamond91.9%—
SimpleQA Verified34.2%—

Multimodal Not comparable

GLM-5.2: —, Hunyuan Large Vision: 35.7 (#83)

Multimodal benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
LMArena Vision—1180

Multilingual GLM-5.2 leads

GLM-5.2: 55.8 (#26), Hunyuan Large Vision: 39.9 (#221)

Multilingual benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
LMArena Non-English14591236
LMArena Chinese15191287
LMArena Russian14661243
LMArena French1479—
LMArena German1468—
LMArena Japanese1451—
LMArena Korean1445—
LMArena Spanish1477—

Instruction Following GLM-5.2 leads

GLM-5.2: 76.9 (#34), Hunyuan Large Vision: 65.8 (#215)

Instruction Following benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
LMArena Instruction Following14651251

Long Context GLM-5.2 leads

GLM-5.2: 45.3 (#43), Hunyuan Large Vision: 38.9 (#189)

Long Context benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
LMArena Longer Query14791280

Writing & Preference GLM-5.2 leads

GLM-5.2: 70.4 (#21), Hunyuan Large Vision: 46.5 (#218)

Writing & Preference benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
LMArena Text14701263
LMArena Creative Writing14621248
LMArena Multi-Turn14691254
EQ-Bench Creative Writing1757—
EQ-Bench 41222—

Frequently asked questions

Is GLM-5.2 better than Hunyuan Large Vision?

GLM-5.2 is the stronger model overall, scoring 51.1 to 37.6 on the Noometry Index.

Is GLM-5.2 or Hunyuan Large Vision better for coding?

GLM-5.2 scores higher on coding benchmarks: 51.3 versus 38.3 in the Noometry coding category.

How many benchmarks do GLM-5.2 and Hunyuan Large Vision share?

12 benchmarks have published results for both models. GLM-5.2 has 51 scored results on Noometry and Hunyuan Large Vision has 13.

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