Noometry

Model comparison

GLM-4.7 vs Qwen3.6 27B

GLM-4.7 and Qwen3.6 27B score almost the same on the Noometry Index (41.7 vs 41.9), so choose on price, context window or the category you care about most.

Last verified . 6 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

41.7

Rank #117 Confirmed

Qwen3.6 27B Alibaba (Qwen)

41.9

Rank #112 Confirmed

Summary

  • They share 6 benchmarks with published results for both. GLM-4.7 scores higher in 2 categories and Qwen3.6 27B in 3 categories; 4 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-4.7 leads 61.1 to 50.3.
  • The biggest single-benchmark swing is Chess Puzzles: 6% for GLM-4.7 and 22% for Qwen3.6 27B.
  • GLM-4.7 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 205K.

Side by side

GLM-4.7Qwen3.6 27B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index41.741.9
Released2025-12-222026-04-22
WeightsOpenOpen
Context window205K262K
Max output131K66K
Input $ / M tokens$0.60$0.60
Output $ / M tokens$2.20$3.60
Results tracked3611

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Category by category

Coding GLM-4.7 leads

GLM-4.7: 43.6 (#74), Qwen3.6 27B: 38.5 (#162)

BenchmarkGLM-4.7Qwen3.6 27B
SciCode45.1%37.3%
LMArena WebDev1435—
LMArena Coding1454—
ALE-Bench399.48—

Agentic & Tool Use Not comparable

GLM-4.7: 26.4 (#96), Qwen3.6 27B: —

BenchmarkGLM-4.7Qwen3.6 27B
Terminal-Bench33.4%—
Vending-Bench 22,377—

Reasoning Too close to call

GLM-4.7: 23.7 (#161), Qwen3.6 27B: 24.4 (#148)

BenchmarkGLM-4.7Qwen3.6 27B
CritPt1.7%0.9%
Chess Puzzles6%22%
Epoch Capabilities Index143.53146.47
SimpleBench47.7%—
LMArena Hard Prompts1443—
Mystery Game Puzzles—7%
DTBench—78.1%
LMCA—34.5%

Math Qwen3.6 27B leads

GLM-4.7: 37.7 (#92), Qwen3.6 27B: 47.5 (#56)

BenchmarkGLM-4.7Qwen3.6 27B
OTIS Mock AIME 2024-202583.3%91.1%
FrontierMath (Tiers 1-3)—35.1%
ProofBench6%—
LMArena Math1423—
FrontierMath (Feb 2025 set)2.4%—
FrontierMath Tier 4 (v1)0%—

Knowledge Qwen3.6 27B leads

GLM-4.7: 47.0 (#74), Qwen3.6 27B: 52.4 (#58)

BenchmarkGLM-4.7Qwen3.6 27B
GPQA Diamond83.3%85.9%
SimpleQA Verified32.2%—
Vectara Hallucination Rate11.7%—
LMArena Expert1424—

Multilingual Not comparable

GLM-4.7: 53.0 (#75), Qwen3.6 27B: —

BenchmarkGLM-4.7Qwen3.6 27B
LMArena Non-English1417—
LMArena Chinese1495—
LMArena French1432—
LMArena German1426—
LMArena Japanese1439—
LMArena Korean1401—
LMArena Russian1423—
LMArena Spanish1433—

Instruction Following Not comparable

GLM-4.7: 74.6 (#90), Qwen3.6 27B: —

BenchmarkGLM-4.7Qwen3.6 27B
LMArena Instruction Following1411—

Long Context Not comparable

GLM-4.7: 42.8 (#111), Qwen3.6 27B: —

BenchmarkGLM-4.7Qwen3.6 27B
CL-bench15.9%—
CL-bench Life10.9%—
LMArena Longer Query1432—

Writing & Preference GLM-4.7 leads

GLM-4.7: 61.1 (#89), Qwen3.6 27B: 50.3 (#180)

BenchmarkGLM-4.7Qwen3.6 27B
LMArena Text1436—
LMArena Creative Writing1401—
EQ-Bench Creative Writing1413—
EQ-Bench 4—1026
LMArena Multi-Turn1446—

Frequently asked questions

Is GLM-4.7 better than Qwen3.6 27B?

GLM-4.7 and Qwen3.6 27B score almost the same on the Noometry Index (41.7 vs 41.9), so choose on price, context window or the category you care about most.

Which is cheaper, GLM-4.7 or Qwen3.6 27B?

GLM-4.7 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-4.7 or Qwen3.6 27B better for coding?

GLM-4.7 scores higher on coding benchmarks: 43.6 versus 38.5 in the Noometry coding category.

Which has the bigger context window?

Qwen3.6 27B does, with 262K tokens against 205K.

How many benchmarks do GLM-4.7 and Qwen3.6 27B share?

6 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Qwen3.6 27B has 11.

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