Noometry

Model comparison

GLM-4.6 vs Qwen3.5-Flash

Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 41.4 on the Noometry Index.

Last verified . 22 shared benchmarks.

GLM-4.6 Z.ai (Zhipu)

41.4

Rank #135 Confirmed

Qwen3.5-Flash Alibaba (Qwen)

42.5

Rank #112 Confirmed

Summary

  • They share 22 benchmarks with published results for both. GLM-4.6 scores higher in 6 categories and Qwen3.5-Flash in 2 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Qwen3.5-Flash leads 33.7 to 23.7.
  • Qwen3.5-Flash is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.60 / $2.20 for GLM-4.6.
  • Qwen3.5-Flash accepts more context: 1M tokens versus 205K.
  • GLM-4.6 has downloadable open weights; the other is API-only.

Side by side

GLM-4.6Qwen3.5-Flash
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index41.442.5
Released2025-09-302026-02-23
WeightsOpenProprietary
Context window205K1M
Max output131K66K
Input $ / M tokens$0.60$0.10
Output $ / M tokens$2.20$0.40
Results tracked2932

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Category by category

Coding GLM-4.6 leads

GLM-4.6: 40.1 (#148), Qwen3.5-Flash: 34.2 (#242)

BenchmarkGLM-4.6Qwen3.5-Flash
LMArena WebDev13401244
LMArena Coding14491412
ALE-Bench340.82221.8
SWE-bench Verified (bash only)55.4%—
SciCode38.4%—

Agentic & Tool Use Not comparable

GLM-4.6: 32.3 (#66), Qwen3.5-Flash: —

BenchmarkGLM-4.6Qwen3.5-Flash
Terminal-Bench24.5%—
Berkeley Function Calling Leaderboard72.4%—
Vending-Bench 2—462.69

Reasoning Qwen3.5-Flash leads

GLM-4.6: 23.7 (#172), Qwen3.5-Flash: 33.7 (#72)

BenchmarkGLM-4.6Qwen3.5-Flash
LMArena Hard Prompts14401403
Kagi LLM Benchmark47.4%—
CritPt1.1%—
Chess Puzzles—21%
Mystery Game Puzzles—20%
DTBench—82.9%
LMCA—29.1%
Epoch Capabilities Index—143.98

Math GLM-4.6 leads

GLM-4.6: 39.1 (#111), Qwen3.5-Flash: 37.4 (#158)

BenchmarkGLM-4.6Qwen3.5-Flash
LMArena Math14321407
FrontierMath (Feb 2025 set)3.8%6.2%
FrontierMath Tier 4 (v1)2.1%0%
FrontierMath (Tiers 1-3)—18.2%
OTIS Mock AIME 2024-2025—84.4%

Knowledge Qwen3.5-Flash leads

GLM-4.6: 40.2 (#124), Qwen3.5-Flash: 43.2 (#93)

BenchmarkGLM-4.6Qwen3.5-Flash
Vectara Hallucination Rate9.5%10.5%
LMArena Expert14311407
GPQA Diamond—82.3%
SimpleQA Verified—20.3%

Multilingual GLM-4.6 leads

GLM-4.6: 53.5 (#66), Qwen3.5-Flash: 50.5 (#121)

BenchmarkGLM-4.6Qwen3.5-Flash
LMArena Non-English14261385
LMArena Chinese14991446
LMArena French14591412
LMArena German14471390
LMArena Japanese13931368
LMArena Korean14001344
LMArena Russian14191379
LMArena Spanish14361400

Instruction Following GLM-4.6 leads

GLM-4.6: 74.3 (#98), Qwen3.5-Flash: 72.6 (#139)

BenchmarkGLM-4.6Qwen3.5-Flash
LMArena Instruction Following14101374

Long Context GLM-4.6 leads

GLM-4.6: 43.4 (#94), Qwen3.5-Flash: 42.4 (#124)

BenchmarkGLM-4.6Qwen3.5-Flash
LMArena Longer Query14221392

Writing & Preference GLM-4.6 leads

GLM-4.6: 61.1 (#90), Qwen3.5-Flash: 57.9 (#122)

BenchmarkGLM-4.6Qwen3.5-Flash
LMArena Text14401397
LMArena Creative Writing14111343
LMArena Multi-Turn14271393
EQ-Bench Creative Writing1411—

Frequently asked questions

Is GLM-4.6 better than Qwen3.5-Flash?

Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 41.4 on the Noometry Index.

Which is cheaper, GLM-4.6 or Qwen3.5-Flash?

Qwen3.5-Flash is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; GLM-4.6 lists at $0.60 and $2.20.

Is GLM-4.6 or Qwen3.5-Flash better for coding?

GLM-4.6 scores higher on coding benchmarks: 40.1 versus 34.2 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5-Flash does, with 1M tokens against 205K.

How many benchmarks do GLM-4.6 and Qwen3.5-Flash share?

22 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Qwen3.5-Flash has 32.

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