Model comparison

GLM-5.2 vs Yi-Large

GLM-5.2 has enough public results to be ranked (#44); Yi-Large does not yet, so treat this comparison as directional.

Last verified . 0 shared benchmarks.

GLM-5.2 Z.ai (Zhipu)

51.1

Rank #44 Confirmed

Yi-Large 01.AI

38.1

Unranked Sparse

Summary

  • The widest gap is in coding, where GLM-5.2 leads 51.3 to 36.7.
  • GLM-5.2 has downloadable open weights; the other is API-only.

Side by side

GLM-5.2 and Yi-Large specifications
GLM-5.2Yi-Large
ProviderZ.ai (Zhipu)01.AI
Noometry Index51.138.1
Released2026-06-132024-05-13
WeightsOpenProprietary
Context window1M—
Max output131K—
Input $ / M tokens$1.40—
Output $ / M tokens$4.40—
Results tracked513

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Category by category

Coding GLM-5.2 leads

GLM-5.2: 51.3 (#41), Yi-Large: 36.7 (#203)

Coding benchmarks
BenchmarkGLM-5.2Yi-Large
SWE-bench Verified78.7%—
DeepSWE43.8%—
FrontierCode24.5%—
LMArena WebDev1603—
SciCode50.5%—
WeirdML70.1%—
BigCodeBench Instruct—37.7%
LMArena Coding1485—
BigCodeBench Complete—47.2%
ALE-Bench1,047—

Agentic & Tool Use Not comparable

GLM-5.2: 32.4 (#63), Yi-Large: —

Agentic & Tool Use benchmarks
BenchmarkGLM-5.2Yi-Large
APEX-Agents45.2%—
τ²-bench Banking37.1%—
PostTrainBench31.7%—
GBAEval0%—
Vending-Bench 28,314—

Reasoning Not comparable

GLM-5.2: 42.3 (#52), Yi-Large: —

Reasoning benchmarks
BenchmarkGLM-5.2Yi-Large
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%—
Epoch Capabilities Index151.78—

Math Not comparable

GLM-5.2: 55.7 (#43), Yi-Large: —

Math benchmarks
BenchmarkGLM-5.2Yi-Large
FrontierMath (Tiers 1-3)59.2%—
FrontierMath Tier 429.3%—
MathArena Final-Answer Competitions67.6%—
OTIS Mock AIME 2024-202586.4%—
ProofBench35%—
LMArena Math1482—

Knowledge Not comparable

GLM-5.2: 57.1 (#40), Yi-Large: —

Knowledge benchmarks
BenchmarkGLM-5.2Yi-Large
GPQA Diamond91.9%—
SimpleQA Verified34.2%—
LMArena Expert1486—
MMLU—79.3%

Multilingual Not comparable

GLM-5.2: 55.8 (#26), Yi-Large: —

Multilingual benchmarks
BenchmarkGLM-5.2Yi-Large
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), Yi-Large: —

Instruction Following benchmarks
BenchmarkGLM-5.2Yi-Large
LMArena Instruction Following1465—

Long Context Not comparable

GLM-5.2: 45.3 (#43), Yi-Large: —

Long Context benchmarks
BenchmarkGLM-5.2Yi-Large
LMArena Longer Query1479—

Writing & Preference Not comparable

GLM-5.2: 70.4 (#21), Yi-Large: —

Writing & Preference benchmarks
BenchmarkGLM-5.2Yi-Large
LMArena Text1470—
LMArena Creative Writing1462—
EQ-Bench Creative Writing1757—
EQ-Bench 41222—
LMArena Multi-Turn1469—

Frequently asked questions

Is GLM-5.2 better than Yi-Large?

GLM-5.2 has enough public results to be ranked (#44); Yi-Large does not yet, so treat this comparison as directional.

Is GLM-5.2 or Yi-Large better for coding?

GLM-5.2 scores higher on coding benchmarks: 51.3 versus 36.7 in the Noometry coding category.

How many benchmarks do GLM-5.2 and Yi-Large share?

0 benchmarks have published results for both models. GLM-5.2 has 51 scored results on Noometry and Yi-Large has 3.

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