Noometry

Model comparison

GLM-4.5V vs Qwen3.6 35B-A3B

GLM-4.5V is the stronger model overall, scoring 39.8 to 37.6 on the Noometry Index. Qwen3.6 35B-A3B costs 1.6× less per token, which makes it the better buy when GLM-4.5V's lead doesn't matter for your workload.

Last verified . 0 shared benchmarks.

GLM-4.5V Z.ai (Zhipu)

39.8

Rank #158 Confirmed

Qwen3.6 35B-A3B Alibaba (Qwen)

37.6

Rank #201 Confirmed

Summary

  • The widest gap is in knowledge, where Qwen3.6 35B-A3B leads 51.3 to 37.5.
  • Qwen3.6 35B-A3B is cheaper at $0.25 / $1.49 per million input/output tokens, against $0.60 / $1.80 for GLM-4.5V.
  • Qwen3.6 35B-A3B accepts more context: 262K tokens versus 64K.

Side by side

GLM-4.5VQwen3.6 35B-A3B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index39.837.6
Released2025-08-112026-04-01
WeightsOpenOpen
Context window64K262K
Max output16K66K
Input $ / M tokens$0.60$0.25
Output $ / M tokens$1.80$1.49
Results tracked1514

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Category by category

Coding GLM-4.5V leads

GLM-4.5V: 39.5 (#155), Qwen3.6 35B-A3B: 37.2 (#196)

BenchmarkGLM-4.5VQwen3.6 35B-A3B
SciCode—35.8%
WeirdML—34.5%
LMArena Coding1347—

Agentic & Tool Use Not comparable

GLM-4.5V: —, Qwen3.6 35B-A3B: 22.1 (#134)

BenchmarkGLM-4.5VQwen3.6 35B-A3B
Terminal-Bench—23%

Reasoning Too close to call

GLM-4.5V: 27.4 (#119), Qwen3.6 35B-A3B: 28.0 (#109)

BenchmarkGLM-4.5VQwen3.6 35B-A3B
Kagi LLM Benchmark59.8%—
NYT Connections (extended)—41.6%
CritPt—0.3%
Chess Puzzles—26%
LMArena Hard Prompts1334—
Mystery Game Puzzles—22%
DTBench—73.9%
LMCA—29.7%
Surface Evolver Bench—44.4%
Epoch Capabilities Index—143.93

Math Qwen3.6 35B-A3B leads

GLM-4.5V: 37.4 (#159), Qwen3.6 35B-A3B: 38.9 (#121)

BenchmarkGLM-4.5VQwen3.6 35B-A3B
FrontierMath (Tiers 1-3)—20.4%
OTIS Mock AIME 2024-2025—86.7%
LMArena Math1354—

Knowledge Qwen3.6 35B-A3B leads

GLM-4.5V: 37.5 (#156), Qwen3.6 35B-A3B: 51.3 (#68)

BenchmarkGLM-4.5VQwen3.6 35B-A3B
GPQA Diamond—84.8%
LMArena Expert1353—

Multimodal Not comparable

GLM-4.5V: 34.3 (#92), Qwen3.6 35B-A3B: —

BenchmarkGLM-4.5VQwen3.6 35B-A3B
LMArena Vision1154—

Multilingual Not comparable

GLM-4.5V: 44.6 (#177), Qwen3.6 35B-A3B: —

BenchmarkGLM-4.5VQwen3.6 35B-A3B
LMArena Non-English1303—
LMArena Chinese1337—
LMArena Russian1298—
LMArena Spanish1336—

Instruction Following Not comparable

GLM-4.5V: 69.2 (#175), Qwen3.6 35B-A3B: —

BenchmarkGLM-4.5VQwen3.6 35B-A3B
LMArena Instruction Following1311—

Long Context Not comparable

GLM-4.5V: 39.6 (#171), Qwen3.6 35B-A3B: —

BenchmarkGLM-4.5VQwen3.6 35B-A3B
LMArena Longer Query1304—

Writing & Preference Not comparable

GLM-4.5V: 52.5 (#170), Qwen3.6 35B-A3B: —

BenchmarkGLM-4.5VQwen3.6 35B-A3B
LMArena Text1333—
LMArena Creative Writing1295—
LMArena Multi-Turn1332—

Frequently asked questions

Is GLM-4.5V better than Qwen3.6 35B-A3B?

GLM-4.5V is the stronger model overall, scoring 39.8 to 37.6 on the Noometry Index. Qwen3.6 35B-A3B costs 1.6× less per token, which makes it the better buy when GLM-4.5V's lead doesn't matter for your workload.

Which is cheaper, GLM-4.5V or Qwen3.6 35B-A3B?

Qwen3.6 35B-A3B is cheaper. It lists at $0.25 per million input tokens and $1.49 per million output tokens; GLM-4.5V lists at $0.60 and $1.80.

Is GLM-4.5V or Qwen3.6 35B-A3B better for coding?

GLM-4.5V scores higher on coding benchmarks: 39.5 versus 37.2 in the Noometry coding category.

Which has the bigger context window?

Qwen3.6 35B-A3B does, with 262K tokens against 64K.

How many benchmarks do GLM-4.5V and Qwen3.6 35B-A3B share?

0 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and Qwen3.6 35B-A3B has 14.

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