Noometry

Model comparison

GLM-5 vs Qwen3 32B

GLM-5 is the stronger model overall, scoring 46.1 to 39.2 on the Noometry Index.

Last verified . 19 shared benchmarks.

GLM-5 Z.ai (Zhipu)

46.1

Rank #66 Confirmed

Qwen3 32B Alibaba (Qwen)

39.2

Rank #172 Confirmed

Summary

  • They share 19 benchmarks with published results for both. GLM-5 scores higher in 8 categories and Qwen3 32B in 1 category; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-5 leads 66.0 to 52.9.
  • The biggest single-benchmark swing is GPQA Diamond: 87.8% for GLM-5 and 65.7% for Qwen3 32B.
  • Qwen3 32B is cheaper at $0.70 / $2.80 per million input/output tokens, against $1 / $3.20 for GLM-5.
  • GLM-5 accepts more context: 205K tokens versus 131K.

Side by side

GLM-5Qwen3 32B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index46.139.2
Released2026-02-112025-04
WeightsOpenOpen
Context window205K131K
Max output131K16K
Input $ / M tokens$1$0.70
Output $ / M tokens$3.20$2.80
Results tracked4526

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Category by category

Coding GLM-5 leads

GLM-5: 49.0 (#52), Qwen3 32B: 37.7 (#190)

BenchmarkGLM-5Qwen3 32B
LMArena Coding14611358
SWE-bench Verified72.1%—
SWE-bench Verified (bash only)72.8%—
Aider Polyglot—40%
LMArena WebDev1434—
SWE-bench Multilingual69.7%—
SciCode—35.4%
WeirdML48.2%—
ALE-Bench765.62—

Agentic & Tool Use Qwen3 32B leads

GLM-5: 31.1 (#71), Qwen3 32B: 32.6 (#62)

BenchmarkGLM-5Qwen3 32B
Terminal-Bench52.4%—
Berkeley Function Calling Leaderboard—48.7%
τ²-bench Airline82.5%—
τ²-bench Banking9.8%—
τ²-bench Retail73.7%—
τ²-bench Telecom86.8%—
Vending-Bench 24,432—

Reasoning GLM-5 leads

GLM-5: 27.6 (#116), Qwen3 32B: 20.2 (#241)

BenchmarkGLM-5Qwen3 32B
Kagi LLM Benchmark75%54.9%
Chess Puzzles10%5%
LMArena Hard Prompts14521334
Epoch Capabilities Index145.83138.51
ARC-AGI-24.9%—
SimpleBench53.2%—
NYT Connections (extended)74.8%—
ARC-AGI-144.7%—
CritPt—0.3%
DTBench—67.5%
LMCA—17.3%
ForecastBench61—

Math GLM-5 leads

GLM-5: 46.4 (#71), Qwen3 32B: 39.7 (#99)

BenchmarkGLM-5Qwen3 32B
OTIS Mock AIME 2024-202580%66.9%
LMArena Math14401399
MathArena Final-Answer Competitions65.7%—
FrontierMath (Feb 2025 set)16.4%—
FrontierMath Tier 4 (v1)2.1%—

Knowledge GLM-5 leads

GLM-5: 52.3 (#64), Qwen3 32B: 40.0 (#125)

BenchmarkGLM-5Qwen3 32B
GPQA Diamond87.8%65.7%
Vectara Hallucination Rate10.1%5.9%
LMArena Expert14541362

Multilingual GLM-5 leads

GLM-5: 53.7 (#58), Qwen3 32B: 45.6 (#167)

BenchmarkGLM-5Qwen3 32B
LMArena Non-English14301317
LMArena Chinese15111357
LMArena German14451341
LMArena Russian14361311
LMArena French1455—
LMArena Japanese1416—
LMArena Korean1423—
LMArena Spanish1454—

Instruction Following GLM-5 leads

GLM-5: 75.2 (#67), Qwen3 32B: 68.9 (#179)

BenchmarkGLM-5Qwen3 32B
LMArena Instruction Following14281305

Long Context Too close to call

GLM-5: 44.7 (#60), Qwen3 32B: 43.8 (#87)

BenchmarkGLM-5Qwen3 32B
LMArena Longer Query14461327
Fiction.LiveBench—74.2%
CL-bench18.7%—

Writing & Preference GLM-5 leads

GLM-5: 66.0 (#38), Qwen3 32B: 52.9 (#163)

BenchmarkGLM-5Qwen3 32B
LMArena Text14461340
LMArena Creative Writing14391297
LMArena Multi-Turn14561331
EQ-Bench Creative Writing1601—

Frequently asked questions

Is GLM-5 better than Qwen3 32B?

GLM-5 is the stronger model overall, scoring 46.1 to 39.2 on the Noometry Index.

Which is cheaper, GLM-5 or Qwen3 32B?

Qwen3 32B is cheaper. It lists at $0.70 per million input tokens and $2.80 per million output tokens; GLM-5 lists at $1 and $3.20.

Is GLM-5 or Qwen3 32B better for coding?

GLM-5 scores higher on coding benchmarks: 49.0 versus 37.7 in the Noometry coding category.

Which has the bigger context window?

GLM-5 does, with 205K tokens against 131K.

How many benchmarks do GLM-5 and Qwen3 32B share?

19 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Qwen3 32B has 26.

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