Model comparison

GLM-5.2 vs Hunyuan Large Vision

GLM-5.2 is the stronger model overall, scoring 50.9 to 37.0 on the Noometry Index.

Last verified . 12 shared benchmarks.

GLM-5.2 Z.ai (Zhipu)

50.9

Rank #38 Confirmed

Hunyuan Large Vision Tencent

37.0

Rank #198 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 70.7 to 46.7.
  • 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 Index50.937.0
Released2026-06-13—
WeightsOpenProprietary
Context window1M—
Max output131K—
Input $ / M tokens$1.40—
Output $ / M tokens$4.40—
Results tracked5013

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Category by category

Coding GLM-5.2 leads

GLM-5.2: 50.9 (#37), Hunyuan Large Vision: 37.6 (#176)

Coding benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
LMArena Coding14841307
SWE-bench Verified78.7%—
DeepSWE43.8%—
FrontierCode24.5%—
LMArena WebDev1604—
SciCode50.5%—
WeirdML70.1%—
ALE-Bench1,047—

Agentic & Tool Use Not comparable

GLM-5.2: 31.6 (#63), Hunyuan Large Vision: —

Agentic & Tool Use benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
τ²-bench Banking37.1%—
PostTrainBench31.7%—
GBAEval0%—
Vending-Bench 28,314—

Reasoning GLM-5.2 leads

GLM-5.2: 42.1 (#46), Hunyuan Large Vision: 23.8 (#160)

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 Index151.76—

Math GLM-5.2 leads

GLM-5.2: 55.4 (#35), Hunyuan Large Vision: 32.8 (#184)

Math benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
LMArena Math14821269
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 (#36), Hunyuan Large Vision: 33.7 (#191)

Knowledge benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
LMArena Expert14841250
GPQA Diamond91.9%—
SimpleQA Verified34.2%—

Multimodal Not comparable

GLM-5.2: —, Hunyuan Large Vision: 35.1 (#79)

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

Multilingual GLM-5.2 leads

GLM-5.2: 56.0 (#25), Hunyuan Large Vision: 40.1 (#216)

Multilingual benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
LMArena Non-English14591236
LMArena Chinese15181289
LMArena Russian14671243
LMArena French1476—
LMArena German1470—
LMArena Japanese1451—
LMArena Korean1445—
LMArena Spanish1477—

Instruction Following GLM-5.2 leads

GLM-5.2: 77.1 (#32), Hunyuan Large Vision: 66.0 (#210)

Instruction Following benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
LMArena Instruction Following14651250

Long Context GLM-5.2 leads

GLM-5.2: 45.3 (#43), Hunyuan Large Vision: 38.8 (#184)

Long Context benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
LMArena Longer Query14791279

Writing & Preference GLM-5.2 leads

GLM-5.2: 70.7 (#20), Hunyuan Large Vision: 46.7 (#211)

Writing & Preference benchmarks
BenchmarkGLM-5.2Hunyuan Large Vision
LMArena Text14701263
LMArena Creative Writing14651250
LMArena Multi-Turn14681253
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 50.9 to 37.0 on the Noometry Index.

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

GLM-5.2 scores higher on coding benchmarks: 50.9 versus 37.6 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 50 scored results on Noometry and Hunyuan Large Vision has 13.

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