Noometry

Model comparison

GLM-4.6V vs Qwen3.5-Flash

Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 41.3 on the Noometry Index.

Last verified . 11 shared benchmarks.

GLM-4.6V Z.ai (Zhipu)

41.3

Rank #137 Confirmed

Qwen3.5-Flash Alibaba (Qwen)

42.5

Rank #112 Confirmed

Summary

  • They share 11 benchmarks with published results for both. GLM-4.6V scores higher in 1 category and Qwen3.5-Flash in 6 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in coding, where GLM-4.6V leads 40.9 to 34.2.
  • Qwen3.5-Flash is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.30 / $0.90 for GLM-4.6V.
  • Qwen3.5-Flash accepts more context: 1M tokens versus 128K.
  • GLM-4.6V has downloadable open weights; the other is API-only.

Side by side

GLM-4.6VQwen3.5-Flash
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index41.342.5
Released2025-12-082026-02-23
WeightsOpenProprietary
Context window128K1M
Max output33K66K
Input $ / M tokens$0.30$0.10
Output $ / M tokens$0.90$0.40
Results tracked1232

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Category by category

Coding GLM-4.6V leads

GLM-4.6V: 40.9 (#128), Qwen3.5-Flash: 34.2 (#242)

BenchmarkGLM-4.6VQwen3.5-Flash
LMArena Coding13901412
LMArena WebDev—1244
ALE-Bench—221.8

Agentic & Tool Use Not comparable

GLM-4.6V: —, Qwen3.5-Flash: —

BenchmarkGLM-4.6VQwen3.5-Flash
Vending-Bench 2—462.69

Reasoning Qwen3.5-Flash leads

GLM-4.6V: 27.6 (#115), Qwen3.5-Flash: 33.7 (#72)

BenchmarkGLM-4.6VQwen3.5-Flash
LMArena Hard Prompts13681403
Chess Puzzles—21%
Mystery Game Puzzles—20%
DTBench—82.9%
LMCA—29.1%
Epoch Capabilities Index—143.98

Math Not comparable

GLM-4.6V: —, Qwen3.5-Flash: 37.4 (#158)

BenchmarkGLM-4.6VQwen3.5-Flash
FrontierMath (Tiers 1-3)—18.2%
OTIS Mock AIME 2024-2025—84.4%
LMArena Math—1407
FrontierMath (Feb 2025 set)—6.2%
FrontierMath Tier 4 (v1)—0%

Knowledge Qwen3.5-Flash leads

GLM-4.6V: 38.0 (#149), Qwen3.5-Flash: 43.2 (#93)

BenchmarkGLM-4.6VQwen3.5-Flash
LMArena Expert13711407
GPQA Diamond—82.3%
SimpleQA Verified—20.3%
Vectara Hallucination Rate—10.5%

Multimodal Not comparable

GLM-4.6V: 34.8 (#90), Qwen3.5-Flash: —

BenchmarkGLM-4.6VQwen3.5-Flash
LMArena Vision1164—

Multilingual Qwen3.5-Flash leads

GLM-4.6V: 48.6 (#141), Qwen3.5-Flash: 50.5 (#121)

BenchmarkGLM-4.6VQwen3.5-Flash
LMArena Non-English13591385
LMArena Chinese14251446
LMArena Russian13401379
LMArena French—1412
LMArena German—1390
LMArena Japanese—1368
LMArena Korean—1344
LMArena Spanish—1400

Instruction Following Qwen3.5-Flash leads

GLM-4.6V: 71.4 (#151), Qwen3.5-Flash: 72.6 (#139)

BenchmarkGLM-4.6VQwen3.5-Flash
LMArena Instruction Following13521374

Long Context Qwen3.5-Flash leads

GLM-4.6V: 41.3 (#143), Qwen3.5-Flash: 42.4 (#124)

BenchmarkGLM-4.6VQwen3.5-Flash
LMArena Longer Query13581392

Writing & Preference Qwen3.5-Flash leads

GLM-4.6V: 56.6 (#137), Qwen3.5-Flash: 57.9 (#122)

BenchmarkGLM-4.6VQwen3.5-Flash
LMArena Text13771397
LMArena Creative Writing13471343
LMArena Multi-Turn13601393

Frequently asked questions

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

Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 41.3 on the Noometry Index.

Which is cheaper, GLM-4.6V 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-4.6V lists at $0.30 and $0.90.

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

GLM-4.6V scores higher on coding benchmarks: 40.9 versus 34.2 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5-Flash does, with 1M tokens against 128K.

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

11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Qwen3.5-Flash has 32.

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