Model comparison

GLM-4.6 vs QwQ-32B

GLM-4.6 is the stronger model overall, scoring 40.9 to 39.4 on the Noometry Index.

Last verified . 18 shared benchmarks.

GLM-4.6 Z.ai (Zhipu)

40.9

Rank #132 Confirmed

QwQ-32B Alibaba (Qwen)

39.4

Rank #153 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GLM-4.6 scores higher in 7 categories and QwQ-32B in 1 category; 6 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-4.6 leads 61.3 to 50.9.

Side by side

GLM-4.6 and QwQ-32B specifications
GLM-4.6QwQ-32B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index40.939.4
Released2025-09-302024-11-28
WeightsOpenOpen
Context window205K—
Max output131K—
Input $ / M tokens$0.60—
Output $ / M tokens$2.20—
Results tracked2936

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Category by category

Coding GLM-4.6 leads

GLM-4.6: 39.9 (#137), QwQ-32B: 34.9 (#220)

Coding benchmarks
BenchmarkGLM-4.6QwQ-32B
LMArena Coding14491333
SWE-bench Verified (bash only)55.4%—
Aider Polyglot—20.9%
LMArena WebDev1339—
SciCode38.4%—
BigCodeBench Instruct—44.6%
LiveBench Coding—72.2%
BigCodeBench Complete—54.4%
ALE-Bench340.82—

Agentic & Tool Use Not comparable

GLM-4.6: 32.1 (#60), QwQ-32B: —

Agentic & Tool Use benchmarks
BenchmarkGLM-4.6QwQ-32B
Terminal-Bench24.5%—
Berkeley Function Calling Leaderboard72.4%—

Reasoning Too close to call

GLM-4.6: 23.1 (#168), QwQ-32B: 22.9 (#171)

Reasoning benchmarks
BenchmarkGLM-4.6QwQ-32B
LMArena Hard Prompts14401326
Kagi LLM Benchmark47.4%—
CritPt1.1%—
Chess Puzzles—5%
LiveBench Reasoning—83.5%
LiveBench Data Analysis—65%
Epoch Capabilities Index—137.6
ForecastBench—58.3
LiveBench—72%

Math Too close to call

GLM-4.6: 36.4 (#115), QwQ-32B: 36.2 (#123)

Math benchmarks
BenchmarkGLM-4.6QwQ-32B
LMArena Math14311359
OTIS Mock AIME 2024-2025—59.2%
LiveBench Math—77.8%
FrontierMath (Feb 2025 set)3.8%—
FrontierMath Tier 4 (v1)2.1%—

Knowledge GLM-4.6 leads

GLM-4.6: 39.6 (#118), QwQ-32B: 37.2 (#150)

Knowledge benchmarks
BenchmarkGLM-4.6QwQ-32B
LMArena Expert14321323
GPQA Diamond—65.3%
Confabulations—15.6%
Vectara Hallucination Rate9.5%—

Multilingual GLM-4.6 leads

GLM-4.6: 53.6 (#62), QwQ-32B: 45.0 (#171)

Multilingual benchmarks
BenchmarkGLM-4.6QwQ-32B
LMArena Non-English14261306
LMArena Chinese15001378
LMArena French14591337
LMArena German14471313
LMArena Japanese13941263
LMArena Korean14011278
LMArena Russian14181297
LMArena Spanish14361353

Instruction Following GLM-4.6 leads

GLM-4.6: 74.5 (#93), QwQ-32B: 72.8 (#131)

Instruction Following benchmarks
BenchmarkGLM-4.6QwQ-32B
LMArena Instruction Following14101297
LiveBench Instruction Following—81.8%

Long Context QwQ-32B leads

GLM-4.6: 43.4 (#91), QwQ-32B: 49.0 (#11)

Long Context benchmarks
BenchmarkGLM-4.6QwQ-32B
LMArena Longer Query14231308
Fiction.LiveBench—83.3%

Writing & Preference GLM-4.6 leads

GLM-4.6: 61.3 (#86), QwQ-32B: 50.9 (#175)

Writing & Preference benchmarks
BenchmarkGLM-4.6QwQ-32B
LMArena Text14401329
LMArena Creative Writing14111288
EQ-Bench Creative Writing14111257
LMArena Multi-Turn14271314
Short-Story Creative Writing—80.2%
LiveBench Language—51.4%

Frequently asked questions

Is GLM-4.6 better than QwQ-32B?

GLM-4.6 is the stronger model overall, scoring 40.9 to 39.4 on the Noometry Index.

Is GLM-4.6 or QwQ-32B better for coding?

GLM-4.6 scores higher on coding benchmarks: 39.9 versus 34.9 in the Noometry coding category.

How many benchmarks do GLM-4.6 and QwQ-32B share?

18 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and QwQ-32B has 36.

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