Noometry

Model comparison

GLM-5.3 vs Qwen3.6 27B

GLM-5.3 is the stronger model overall, scoring 54.8 to 42.2 on the Noometry Index. Qwen3.6 27B costs 1.6× less per token, which makes it the better buy when GLM-5.3's lead doesn't matter for your workload.

Last verified . 10 shared benchmarks.

GLM-5.3 Z.ai (Zhipu)

54.8

Rank #26 Confirmed

Qwen3.6 27B Alibaba (Qwen)

42.2

Rank #117 Confirmed

Summary

  • They share 10 benchmarks with published results for both. GLM-5.3 scores higher in 5 categories and Qwen3.6 27B in 0 categories; 5 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-5.3 leads 75.7 to 50.3.
  • The biggest single-benchmark swing is FrontierMath (Tiers 1-3): 68.8% for GLM-5.3 and 35.1% for Qwen3.6 27B.
  • Qwen3.6 27B is cheaper at $0.60 / $3.60 per million input/output tokens, against $1.40 / $4.40 for GLM-5.3.
  • GLM-5.3 accepts more context: 1M tokens versus 262K.

Side by side

GLM-5.3Qwen3.6 27B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index54.842.2
Released2026-08-142026-04-22
WeightsOpenOpen
Context window1M262K
Max output131K66K
Input $ / M tokens$1.40$0.60
Output $ / M tokens$4.40$3.60
Results tracked4211

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Category by category

Coding GLM-5.3 leads

GLM-5.3: 59.5 (#14), Qwen3.6 27B: 39.1 (#163)

BenchmarkGLM-5.3Qwen3.6 27B
SciCode59%37.3%
DeepSWE69%—
FrontierCode40.1%—
CursorBench42.6%—
LMArena WebDev1622—
FrontierSWE30.2%—
WeirdML75.4%—
LMArena Coding1496—
ALE-Bench1,317—

Agentic & Tool Use Not comparable

GLM-5.3: 36.4 (#38), Qwen3.6 27B: —

BenchmarkGLM-5.3Qwen3.6 27B
APEX-Agents56.6%—
Vending-Bench 28,164—

Reasoning GLM-5.3 leads

GLM-5.3: 46.1 (#46), Qwen3.6 27B: 25.0 (#153)

BenchmarkGLM-5.3Qwen3.6 27B
CritPt19.1%0.9%
Chess Puzzles21%22%
Mystery Game Puzzles33%7%
DTBench87.7%78.1%
LMCA55.5%34.5%
Epoch Capabilities Index155.61146.5
NYT Connections (extended)74.2%—
LMArena Hard Prompts1489—
Bench to the Future 30.15—

Math GLM-5.3 leads

GLM-5.3: 62.3 (#33), Qwen3.6 27B: 48.5 (#62)

BenchmarkGLM-5.3Qwen3.6 27B
FrontierMath (Tiers 1-3)68.8%35.1%
OTIS Mock AIME 2024-202591.1%91.1%
FrontierMath Tier 429.3%—
ProofBench49%—
LMArena Math1489—

Knowledge GLM-5.3 leads

GLM-5.3: 58.3 (#37), Qwen3.6 27B: 52.4 (#63)

BenchmarkGLM-5.3Qwen3.6 27B
GPQA Diamond90.9%85.9%
SimpleQA Verified41%—
LMArena Expert1516—

Multilingual Not comparable

GLM-5.3: 55.7 (#28), Qwen3.6 27B: —

BenchmarkGLM-5.3Qwen3.6 27B
LMArena Non-English1457—
LMArena Chinese1528—
LMArena French1499—
LMArena German1499—
LMArena Japanese1453—
LMArena Korean1472—
LMArena Russian1463—
LMArena Spanish1460—

Instruction Following Not comparable

GLM-5.3: 77.5 (#23), Qwen3.6 27B: —

BenchmarkGLM-5.3Qwen3.6 27B
LMArena Instruction Following1477—

Long Context Not comparable

GLM-5.3: 45.4 (#41), Qwen3.6 27B: —

BenchmarkGLM-5.3Qwen3.6 27B
LMArena Longer Query1482—

Writing & Preference GLM-5.3 leads

GLM-5.3: 75.7 (#6), Qwen3.6 27B: 50.3 (#181)

BenchmarkGLM-5.3Qwen3.6 27B
LMArena Text1471—
LMArena Creative Writing1457—
EQ-Bench Creative Writing2075—
EQ-Bench 4—1026
LMArena Multi-Turn1472—

Frequently asked questions

Is GLM-5.3 better than Qwen3.6 27B?

GLM-5.3 is the stronger model overall, scoring 54.8 to 42.2 on the Noometry Index. Qwen3.6 27B costs 1.6× less per token, which makes it the better buy when GLM-5.3's lead doesn't matter for your workload.

Which is cheaper, GLM-5.3 or Qwen3.6 27B?

Qwen3.6 27B is cheaper. It lists at $0.60 per million input tokens and $3.60 per million output tokens; GLM-5.3 lists at $1.40 and $4.40.

Is GLM-5.3 or Qwen3.6 27B better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.5 versus 39.1 in the Noometry coding category.

Which has the bigger context window?

GLM-5.3 does, with 1M tokens against 262K.

How many benchmarks do GLM-5.3 and Qwen3.6 27B share?

10 benchmarks have published results for both models. GLM-5.3 has 42 scored results on Noometry and Qwen3.6 27B has 11.

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