Noometry

Model comparison

GLM-4.7-Flash vs Qwen3.5-Flash

Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 38.8 on the Noometry Index.

Last verified . 20 shared benchmarks.

GLM-4.7-Flash Z.ai (Zhipu)

38.8

Rank #180 Confirmed

Qwen3.5-Flash Alibaba (Qwen)

42.5

Rank #112 Confirmed

Summary

  • They share 20 benchmarks with published results for both. GLM-4.7-Flash scores higher in 1 category and Qwen3.5-Flash in 7 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Qwen3.5-Flash leads 33.7 to 20.9.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 58.3% for GLM-4.7-Flash and 84.4% for Qwen3.5-Flash.
  • GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.10 / $0.40 for Qwen3.5-Flash.
  • Qwen3.5-Flash accepts more context: 1M tokens versus 200K.
  • GLM-4.7-Flash has downloadable open weights; the other is API-only.

Side by side

GLM-4.7-FlashQwen3.5-Flash
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index38.842.5
Released2026-01-192026-02-23
WeightsOpenProprietary
Context window200K1M
Max output131K66K
Input $ / M tokens$0.06$0.10
Output $ / M tokens$0.40$0.40
Results tracked2132

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Category by category

Coding GLM-4.7-Flash leads

GLM-4.7-Flash: 40.6 (#135), Qwen3.5-Flash: 34.2 (#242)

BenchmarkGLM-4.7-FlashQwen3.5-Flash
LMArena Coding13831412
LMArena WebDev—1244
ALE-Bench—221.8

Agentic & Tool Use Not comparable

GLM-4.7-Flash: —, Qwen3.5-Flash: —

BenchmarkGLM-4.7-FlashQwen3.5-Flash
Vending-Bench 2—462.69

Reasoning Qwen3.5-Flash leads

GLM-4.7-Flash: 20.9 (#229), Qwen3.5-Flash: 33.7 (#72)

BenchmarkGLM-4.7-FlashQwen3.5-Flash
Chess Puzzles0%21%
LMArena Hard Prompts13561403
Mystery Game Puzzles—20%
DTBench—82.9%
LMCA—29.1%
Epoch Capabilities Index—143.98

Math Qwen3.5-Flash leads

GLM-4.7-Flash: 36.1 (#173), Qwen3.5-Flash: 37.4 (#158)

BenchmarkGLM-4.7-FlashQwen3.5-Flash
OTIS Mock AIME 2024-202558.3%84.4%
LMArena Math13551407
FrontierMath (Tiers 1-3)—18.2%
FrontierMath (Feb 2025 set)—6.2%
FrontierMath Tier 4 (v1)—0%

Knowledge Qwen3.5-Flash leads

GLM-4.7-Flash: 35.5 (#184), Qwen3.5-Flash: 43.2 (#93)

BenchmarkGLM-4.7-FlashQwen3.5-Flash
GPQA Diamond60.5%82.3%
Vectara Hallucination Rate9.3%10.5%
LMArena Expert13571407
SimpleQA Verified—20.3%

Multilingual Qwen3.5-Flash leads

GLM-4.7-Flash: 46.5 (#158), Qwen3.5-Flash: 50.5 (#121)

BenchmarkGLM-4.7-FlashQwen3.5-Flash
LMArena Non-English13301385
LMArena Chinese14031446
LMArena French13321412
LMArena German13371390
LMArena Korean12831344
LMArena Russian13321379
LMArena Spanish13501400
LMArena Japanese—1368

Instruction Following Qwen3.5-Flash leads

GLM-4.7-Flash: 70.1 (#167), Qwen3.5-Flash: 72.6 (#139)

BenchmarkGLM-4.7-FlashQwen3.5-Flash
LMArena Instruction Following13271374

Long Context Qwen3.5-Flash leads

GLM-4.7-Flash: 40.9 (#148), Qwen3.5-Flash: 42.4 (#124)

BenchmarkGLM-4.7-FlashQwen3.5-Flash
LMArena Longer Query13451392

Writing & Preference Qwen3.5-Flash leads

GLM-4.7-Flash: 47.4 (#210), Qwen3.5-Flash: 57.9 (#122)

BenchmarkGLM-4.7-FlashQwen3.5-Flash
LMArena Text13511397
LMArena Creative Writing12971343
LMArena Multi-Turn13421393
EQ-Bench Creative Writing1125—

Frequently asked questions

Is GLM-4.7-Flash better than Qwen3.5-Flash?

Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 38.8 on the Noometry Index.

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

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; Qwen3.5-Flash lists at $0.10 and $0.40.

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

GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 34.2 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5-Flash does, with 1M tokens against 200K.

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

20 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Qwen3.5-Flash has 32.

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