Noometry

Model comparison

GLM-4.7 vs Qwen3.5-9B

GLM-4.7 is the stronger model overall, scoring 42.0 to 33.8 on the Noometry Index. Qwen3.5-9B costs 8.9× less per token, which makes it the better buy when GLM-4.7's lead doesn't matter for your workload.

Last verified . 7 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

42.0

Rank #124 Confirmed

Qwen3.5-9B Alibaba (Qwen)

33.8

Rank #236 Confirmed

Summary

  • They share 7 benchmarks with published results for both. GLM-4.7 scores higher in 5 categories and Qwen3.5-9B in 0 categories; 5 gaps are clear of the uncertainty.
  • The widest gap is in agentic & tool use, where GLM-4.7 leads 26.5 to 14.5.
  • The biggest single-benchmark swing is Terminal-Bench: 33.4% for GLM-4.7 and 9.2% for Qwen3.5-9B.
  • Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $0.60 / $2.20 for GLM-4.7.
  • Qwen3.5-9B accepts more context: 262K tokens versus 205K.

Side by side

GLM-4.7Qwen3.5-9B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index42.033.8
Released2025-12-222026-02-23
WeightsOpenOpen
Context window205K262K
Max output131K66K
Input $ / M tokens$0.60$0.10
Output $ / M tokens$2.20$0.15
Results tracked3610

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Category by category

Coding GLM-4.7 leads

GLM-4.7: 44.0 (#79), Qwen3.5-9B: 35.9 (#217)

BenchmarkGLM-4.7Qwen3.5-9B
SciCode45.1%27.5%
LMArena WebDev1435—
LMArena Coding1454—
ALE-Bench399.48—

Agentic & Tool Use GLM-4.7 leads

GLM-4.7: 26.5 (#103), Qwen3.5-9B: 14.5 (#151)

BenchmarkGLM-4.7Qwen3.5-9B
Terminal-Bench33.4%9.2%
Vending-Bench 22,377—

Reasoning GLM-4.7 leads

GLM-4.7: 24.3 (#164), Qwen3.5-9B: 23.1 (#182)

BenchmarkGLM-4.7Qwen3.5-9B
CritPt1.7%0.3%
Chess Puzzles6%12%
Epoch Capabilities Index143.51139.46
SimpleBench47.7%—
LMArena Hard Prompts1443—
DTBench—71.2%
LMCA—24.5%

Math GLM-4.7 leads

GLM-4.7: 38.6 (#135), Qwen3.5-9B: 34.8 (#192)

BenchmarkGLM-4.7Qwen3.5-9B
OTIS Mock AIME 2024-202583.3%61.7%
MathArena Final-Answer Competitions—48.5%
ProofBench6%—
LMArena Math1423—
FrontierMath (Feb 2025 set)2.4%—
FrontierMath Tier 4 (v1)0%—

Knowledge GLM-4.7 leads

GLM-4.7: 47.0 (#80), Qwen3.5-9B: 46.0 (#84)

BenchmarkGLM-4.7Qwen3.5-9B
GPQA Diamond83.3%79%
SimpleQA Verified32.2%—
Vectara Hallucination Rate11.7%—
LMArena Expert1424—

Multilingual Not comparable

GLM-4.7: 52.8 (#79), Qwen3.5-9B: —

BenchmarkGLM-4.7Qwen3.5-9B
LMArena Non-English1417—
LMArena Chinese1495—
LMArena French1432—
LMArena German1424—
LMArena Japanese1439—
LMArena Korean1399—
LMArena Russian1423—
LMArena Spanish1434—

Instruction Following Not comparable

GLM-4.7: 74.4 (#95), Qwen3.5-9B: —

BenchmarkGLM-4.7Qwen3.5-9B
LMArena Instruction Following1411—

Long Context Not comparable

GLM-4.7: 42.8 (#116), Qwen3.5-9B: —

BenchmarkGLM-4.7Qwen3.5-9B
CL-bench15.9%—
CL-bench Life10.9%—
LMArena Longer Query1432—

Writing & Preference Not comparable

GLM-4.7: 60.9 (#93), Qwen3.5-9B: —

BenchmarkGLM-4.7Qwen3.5-9B
LMArena Text1435—
LMArena Creative Writing1401—
EQ-Bench Creative Writing1413—
LMArena Multi-Turn1446—

Frequently asked questions

Is GLM-4.7 better than Qwen3.5-9B?

GLM-4.7 is the stronger model overall, scoring 42.0 to 33.8 on the Noometry Index. Qwen3.5-9B costs 8.9× less per token, which makes it the better buy when GLM-4.7's lead doesn't matter for your workload.

Which is cheaper, GLM-4.7 or Qwen3.5-9B?

Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; GLM-4.7 lists at $0.60 and $2.20.

Is GLM-4.7 or Qwen3.5-9B better for coding?

GLM-4.7 scores higher on coding benchmarks: 44.0 versus 35.9 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5-9B does, with 262K tokens against 205K.

How many benchmarks do GLM-4.7 and Qwen3.5-9B share?

7 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Qwen3.5-9B has 10.

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