Model comparison

GLM-4.5 vs Qwen3.6 27B

GLM-4.5 and Qwen3.6 27B score almost the same on the Noometry Index (41.4 vs 41.9), so choose on price, context window or the category you care about most.

Last verified . 0 shared benchmarks.

GLM-4.5 Z.ai (Zhipu)

41.4

Rank #125 Confirmed

Qwen3.6 27B Alibaba (Qwen)

41.9

Rank #112 Confirmed

Summary

  • The widest gap is in knowledge, where Qwen3.6 27B leads 52.4 to 35.5.
  • GLM-4.5 is cheaper at $0.60 / $2.20 per million input/output tokens, against $0.60 / $3.60 for Qwen3.6 27B.
  • Qwen3.6 27B accepts more context: 262K tokens versus 131K.

Side by side

GLM-4.5 and Qwen3.6 27B specifications
GLM-4.5Qwen3.6 27B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index41.441.9
Released2025-07-272026-04-22
WeightsOpenOpen
Context window131K262K
Max output98K66K
Input $ / M tokens$0.60$0.60
Output $ / M tokens$2.20$3.60
Results tracked2711

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Category by category

Coding GLM-4.5 leads

GLM-4.5: 41.1 (#121), Qwen3.6 27B: 38.5 (#162)

Coding benchmarks
BenchmarkGLM-4.5Qwen3.6 27B
SWE-bench Verified (bash only)54.2%—
SciCode—37.3%
WeirdML40.6%—
LMArena Coding1434—
ALE-Bench344.82—
AlgoTune1.52—

Reasoning GLM-4.5 leads

GLM-4.5: 27.7 (#99), Qwen3.6 27B: 24.4 (#148)

Reasoning benchmarks
BenchmarkGLM-4.5Qwen3.6 27B
Kagi LLM Benchmark57.9%—
CritPt—0.9%
Chess Puzzles—22%
LMArena Hard Prompts1430—
Mystery Game Puzzles—7%
DTBench—78.1%
LMCA—34.5%
Epoch Capabilities Index—146.47

Math Qwen3.6 27B leads

GLM-4.5: 36.3 (#119), Qwen3.6 27B: 47.5 (#56)

Math benchmarks
BenchmarkGLM-4.5Qwen3.6 27B
FrontierMath (Tiers 1-3)—35.1%
OTIS Mock AIME 2024-2025—91.1%
LMArena Math1427—

Knowledge Qwen3.6 27B leads

GLM-4.5: 35.5 (#172), Qwen3.6 27B: 52.4 (#58)

Knowledge benchmarks
BenchmarkGLM-4.5Qwen3.6 27B
GPQA Diamond—85.9%
Humanity's Last Exam8.3%—
Confabulations11.3%—
LMArena Expert1433—

Multilingual Not comparable

GLM-4.5: 53.0 (#74), Qwen3.6 27B: —

Multilingual benchmarks
BenchmarkGLM-4.5Qwen3.6 27B
LMArena Non-English1417—
LMArena Chinese1465—
LMArena French1423—
LMArena German1406—
LMArena Japanese1416—
LMArena Korean1382—
LMArena Russian1414—
LMArena Spanish1454—

Instruction Following Not comparable

GLM-4.5: 74.3 (#100), Qwen3.6 27B: —

Instruction Following benchmarks
BenchmarkGLM-4.5Qwen3.6 27B
LMArena Instruction Following1405—

Long Context Not comparable

GLM-4.5: 38.2 (#196), Qwen3.6 27B: —

Long Context benchmarks
BenchmarkGLM-4.5Qwen3.6 27B
Fiction.LiveBench58.3%—
LMArena Longer Query1413—

Writing & Preference GLM-4.5 leads

GLM-4.5: 57.7 (#121), Qwen3.6 27B: 50.3 (#180)

Writing & Preference benchmarks
BenchmarkGLM-4.5Qwen3.6 27B
LMArena Text1430—
LMArena Creative Writing1395—
Short-Story Creative Writing73.4%—
EQ-Bench Creative Writing1343—
EQ-Bench 4—1026
LMArena Multi-Turn1415—

Frequently asked questions

Is GLM-4.5 better than Qwen3.6 27B?

GLM-4.5 and Qwen3.6 27B score almost the same on the Noometry Index (41.4 vs 41.9), so choose on price, context window or the category you care about most.

Which is cheaper, GLM-4.5 or Qwen3.6 27B?

GLM-4.5 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Qwen3.6 27B lists at $0.60 and $3.60.

Is GLM-4.5 or Qwen3.6 27B better for coding?

GLM-4.5 scores higher on coding benchmarks: 41.1 versus 38.5 in the Noometry coding category.

Which has the bigger context window?

Qwen3.6 27B does, with 262K tokens against 131K.

How many benchmarks do GLM-4.5 and Qwen3.6 27B share?

0 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Qwen3.6 27B has 11.

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