Model comparison

GLM-5.2 vs Olmo 3.1 32b Instruct

GLM-5.2 is the stronger model overall, scoring 51.1 to 39.4 on the Noometry Index.

Last verified . 16 shared benchmarks.

GLM-5.2 Z.ai (Zhipu)

51.1

Rank #44 Confirmed

Summary

  • They share 16 benchmarks with published results for both. GLM-5.2 scores higher in 8 categories and Olmo 3.1 32b Instruct in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-5.2 leads 57.1 to 36.1.

Side by side

GLM-5.2 and Olmo 3.1 32b Instruct specifications
GLM-5.2Olmo 3.1 32b Instruct
ProviderZ.ai (Zhipu)Allen Institute for AI (Ai2)
Noometry Index51.139.4
Released2026-06-13—
WeightsOpenOpen
Context window1M—
Max output131K—
Input $ / M tokens$1.40—
Output $ / M tokens$4.40—
Results tracked5116

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Category by category

Coding GLM-5.2 leads

GLM-5.2: 51.3 (#41), Olmo 3.1 32b Instruct: 39.5 (#157)

Coding benchmarks
BenchmarkGLM-5.2Olmo 3.1 32b Instruct
LMArena Coding14851347
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), Olmo 3.1 32b Instruct: —

Agentic & Tool Use benchmarks
BenchmarkGLM-5.2Olmo 3.1 32b Instruct
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), Olmo 3.1 32b Instruct: 26.4 (#132)

Reasoning benchmarks
BenchmarkGLM-5.2Olmo 3.1 32b Instruct
LMArena Hard Prompts14801322
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), Olmo 3.1 32b Instruct: 36.3 (#167)

Math benchmarks
BenchmarkGLM-5.2Olmo 3.1 32b Instruct
LMArena Math14821305
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), Olmo 3.1 32b Instruct: 36.1 (#175)

Knowledge benchmarks
BenchmarkGLM-5.2Olmo 3.1 32b Instruct
LMArena Expert14861308
GPQA Diamond91.9%—
SimpleQA Verified34.2%—

Multilingual GLM-5.2 leads

GLM-5.2: 55.8 (#26), Olmo 3.1 32b Instruct: 42.6 (#191)

Multilingual benchmarks
BenchmarkGLM-5.2Olmo 3.1 32b Instruct
LMArena Non-English14591275
LMArena Chinese15191304
LMArena French14791328
LMArena German14681282
LMArena Korean14451206
LMArena Russian14661268
LMArena Spanish14771336
LMArena Japanese1451—

Instruction Following GLM-5.2 leads

GLM-5.2: 76.9 (#34), Olmo 3.1 32b Instruct: 68.6 (#187)

Instruction Following benchmarks
BenchmarkGLM-5.2Olmo 3.1 32b Instruct
LMArena Instruction Following14651299

Long Context GLM-5.2 leads

GLM-5.2: 45.3 (#43), Olmo 3.1 32b Instruct: 39.9 (#166)

Long Context benchmarks
BenchmarkGLM-5.2Olmo 3.1 32b Instruct
LMArena Longer Query14791312

Writing & Preference GLM-5.2 leads

GLM-5.2: 70.4 (#21), Olmo 3.1 32b Instruct: 50.2 (#185)

Writing & Preference benchmarks
BenchmarkGLM-5.2Olmo 3.1 32b Instruct
LMArena Text14701311
LMArena Creative Writing14621264
LMArena Multi-Turn14691309
EQ-Bench Creative Writing1757—
EQ-Bench 41222—

Frequently asked questions

Is GLM-5.2 better than Olmo 3.1 32b Instruct?

GLM-5.2 is the stronger model overall, scoring 51.1 to 39.4 on the Noometry Index.

Is GLM-5.2 or Olmo 3.1 32b Instruct better for coding?

GLM-5.2 scores higher on coding benchmarks: 51.3 versus 39.5 in the Noometry coding category.

How many benchmarks do GLM-5.2 and Olmo 3.1 32b Instruct share?

16 benchmarks have published results for both models. GLM-5.2 has 51 scored results on Noometry and Olmo 3.1 32b Instruct has 16.

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