Noometry

Model comparison

GLM-4.5 vs Qwen3.5 27B

GLM-4.5 and Qwen3.5 27B score almost the same on the Noometry Index (42.0 vs 41.9), so choose on price, context window or the category you care about most.

Last verified . 19 shared benchmarks.

GLM-4.5 Z.ai (Zhipu)

42.0

Rank #122 Confirmed

Qwen3.5 27B Alibaba (Qwen)

41.9

Rank #127 Confirmed

Summary

  • They share 19 benchmarks with published results for both. GLM-4.5 scores higher in 5 categories and Qwen3.5 27B in 3 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in long context, where Qwen3.5 27B leads 43.1 to 38.2.
  • Qwen3.5 27B is cheaper at $0.30 / $2.40 per million input/output tokens, against $0.60 / $2.20 for GLM-4.5.
  • Qwen3.5 27B accepts more context: 262K tokens versus 131K.

Side by side

GLM-4.5Qwen3.5 27B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index42.041.9
Released2025-07-272026-02-23
WeightsOpenOpen
Context window131K262K
Max output98K66K
Input $ / M tokens$0.60$0.30
Output $ / M tokens$2.20$2.40
Results tracked2728

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Category by category

Coding GLM-4.5 leads

GLM-4.5: 41.4 (#125), Qwen3.5 27B: 38.9 (#168)

BenchmarkGLM-4.5Qwen3.5 27B
WeirdML40.6%39.5%
LMArena Coding14341427
ALE-Bench344.82349.45
SWE-bench Verified (bash only)54.2%—
LMArena WebDev—1358
AlgoTune1.52—

Agentic & Tool Use Not comparable

GLM-4.5: —, Qwen3.5 27B: —

BenchmarkGLM-4.5Qwen3.5 27B
Vending-Bench 2—201.98

Reasoning GLM-4.5 leads

GLM-4.5: 28.6 (#100), Qwen3.5 27B: 27.5 (#117)

BenchmarkGLM-4.5Qwen3.5 27B
LMArena Hard Prompts14291414
Kagi LLM Benchmark57.9%—
NYT Connections (extended)—47.9%
Thematic Generalization—45.5%
DTBench—82.4%
LMCA—34%

Math Too close to call

GLM-4.5: 39.0 (#116), Qwen3.5 27B: 38.8 (#127)

BenchmarkGLM-4.5Qwen3.5 27B
LMArena Math14271429
MathArena Final-Answer Competitions—56.7%

Knowledge Qwen3.5 27B leads

GLM-4.5: 35.9 (#179), Qwen3.5 27B: 38.0 (#150)

BenchmarkGLM-4.5Qwen3.5 27B
LMArena Expert14331428
Humanity's Last Exam8.3%—
Confabulations11.3%—
Vectara Hallucination Rate—12.1%

Multimodal Not comparable

GLM-4.5: —, Qwen3.5 27B: 39.4 (#59)

BenchmarkGLM-4.5Qwen3.5 27B
LMArena Vision—1241

Multilingual GLM-4.5 leads

GLM-4.5: 52.8 (#77), Qwen3.5 27B: 50.8 (#115)

BenchmarkGLM-4.5Qwen3.5 27B
LMArena Non-English14171390
LMArena Chinese14651478
LMArena French14181410
LMArena German14071393
LMArena Japanese14151345
LMArena Korean13801358
LMArena Russian14141390
LMArena Spanish14541407

Instruction Following Too close to call

GLM-4.5: 74.1 (#104), Qwen3.5 27B: 73.5 (#119)

BenchmarkGLM-4.5Qwen3.5 27B
LMArena Instruction Following14041393

Long Context Qwen3.5 27B leads

GLM-4.5: 38.2 (#201), Qwen3.5 27B: 43.1 (#106)

BenchmarkGLM-4.5Qwen3.5 27B
LMArena Longer Query14121413
Fiction.LiveBench58.3%—

Writing & Preference Qwen3.5 27B leads

GLM-4.5: 57.5 (#127), Qwen3.5 27B: 59.3 (#111)

BenchmarkGLM-4.5Qwen3.5 27B
LMArena Text14301409
LMArena Creative Writing13951362
LMArena Multi-Turn14151410
Short-Story Creative Writing73.4%—
EQ-Bench Creative Writing1343—

Frequently asked questions

Is GLM-4.5 better than Qwen3.5 27B?

GLM-4.5 and Qwen3.5 27B score almost the same on the Noometry Index (42.0 vs 41.9), so choose on price, context window or the category you care about most.

Which is cheaper, GLM-4.5 or Qwen3.5 27B?

Qwen3.5 27B is cheaper. It lists at $0.30 per million input tokens and $2.40 per million output tokens; GLM-4.5 lists at $0.60 and $2.20.

Is GLM-4.5 or Qwen3.5 27B better for coding?

GLM-4.5 scores higher on coding benchmarks: 41.4 versus 38.9 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5 27B does, with 262K tokens against 131K.

How many benchmarks do GLM-4.5 and Qwen3.5 27B share?

19 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Qwen3.5 27B has 28.

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