Noometry

Model comparison

GLM-4.6V vs Qwen3-30B-A3B

GLM-4.6V is the stronger model overall, scoring 40.9 to 38.5 on the Noometry Index. Qwen3-30B-A3B costs 2.1× less per token, which makes it the better buy when GLM-4.6V's lead doesn't matter for your workload.

Last verified . 11 shared benchmarks.

GLM-4.6V Z.ai (Zhipu)

40.9

Rank #133 Confirmed

Qwen3-30B-A3B Alibaba (Qwen)

38.5

Rank #174 Confirmed

Summary

  • They share 11 benchmarks with published results for both. GLM-4.6V scores higher in 4 categories and Qwen3-30B-A3B in 3 categories; 4 gaps are clear of the uncertainty.
  • The widest gap is in long context, where GLM-4.6V leads 41.3 to 31.0.
  • Qwen3-30B-A3B is cheaper at $0.12 / $0.50 per million input/output tokens, against $0.30 / $0.90 for GLM-4.6V.
  • GLM-4.6V accepts more context: 128K tokens versus 41K.

Side by side

GLM-4.6VQwen3-30B-A3B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index40.938.5
Released2025-12-082025-04-28
WeightsOpenOpen
Context window128K41K
Max output33K16K
Input $ / M tokens$0.30$0.12
Output $ / M tokens$0.90$0.50
Results tracked1232

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Category by category

Coding GLM-4.6V leads

GLM-4.6V: 40.2 (#128), Qwen3-30B-A3B: 37.0 (#188)

BenchmarkGLM-4.6VQwen3-30B-A3B
LMArena Coding13901416
SciCode—33.3%
WeirdML—29.8%

Agentic & Tool Use Not comparable

GLM-4.6V: —, Qwen3-30B-A3B: 29.5 (#75)

BenchmarkGLM-4.6VQwen3-30B-A3B
Berkeley Function Calling Leaderboard—41.4%

Reasoning GLM-4.6V leads

GLM-4.6V: 26.5 (#117), Qwen3-30B-A3B: 21.6 (#193)

BenchmarkGLM-4.6VQwen3-30B-A3B
LMArena Hard Prompts13681398
Kagi LLM Benchmark—54.9%
CritPt—0.3%
Chess Puzzles—8%
DTBench—69.3%
LMCA—22.4%
Epoch Capabilities Index—139.63

Math Not comparable

GLM-4.6V: —, Qwen3-30B-A3B: 36.0 (#133)

BenchmarkGLM-4.6VQwen3-30B-A3B
MathArena Final-Answer Competitions—47.8%
OTIS Mock AIME 2024-2025—70.3%
LMArena Math—1394

Knowledge Qwen3-30B-A3B leads

GLM-4.6V: 37.4 (#148), Qwen3-30B-A3B: 41.7 (#96)

BenchmarkGLM-4.6VQwen3-30B-A3B
LMArena Expert13721395
GPQA Diamond—70.1%
Confabulations—12.3%

Multimodal Not comparable

GLM-4.6V: 34.2 (#83), Qwen3-30B-A3B: —

BenchmarkGLM-4.6VQwen3-30B-A3B
LMArena Vision1164—

Multilingual Too close to call

GLM-4.6V: 48.8 (#135), Qwen3-30B-A3B: 49.8 (#126)

BenchmarkGLM-4.6VQwen3-30B-A3B
LMArena Non-English13591372
LMArena Chinese14261434
LMArena Russian13411369
LMArena French—1419
LMArena German—1379
LMArena Japanese—1338
LMArena Korean—1333
LMArena Spanish—1403

Instruction Following Too close to call

GLM-4.6V: 71.6 (#145), Qwen3-30B-A3B: 72.2 (#137)

BenchmarkGLM-4.6VQwen3-30B-A3B
LMArena Instruction Following13511364

Long Context GLM-4.6V leads

GLM-4.6V: 41.3 (#138), Qwen3-30B-A3B: 31.0 (#278)

BenchmarkGLM-4.6VQwen3-30B-A3B
LMArena Longer Query13581379
Fiction.LiveBench—40.6%

Writing & Preference Too close to call

GLM-4.6V: 56.8 (#132), Qwen3-30B-A3B: 55.9 (#138)

BenchmarkGLM-4.6VQwen3-30B-A3B
LMArena Text13771384
LMArena Creative Writing13471318
LMArena Multi-Turn13591378
Short-Story Creative Writing—75.3%

Frequently asked questions

Is GLM-4.6V better than Qwen3-30B-A3B?

GLM-4.6V is the stronger model overall, scoring 40.9 to 38.5 on the Noometry Index. Qwen3-30B-A3B costs 2.1× less per token, which makes it the better buy when GLM-4.6V's lead doesn't matter for your workload.

Which is cheaper, GLM-4.6V or Qwen3-30B-A3B?

Qwen3-30B-A3B is cheaper. It lists at $0.12 per million input tokens and $0.50 per million output tokens; GLM-4.6V lists at $0.30 and $0.90.

Is GLM-4.6V or Qwen3-30B-A3B better for coding?

GLM-4.6V scores higher on coding benchmarks: 40.2 versus 37.0 in the Noometry coding category.

Which has the bigger context window?

GLM-4.6V does, with 128K tokens against 41K.

How many benchmarks do GLM-4.6V and Qwen3-30B-A3B share?

11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Qwen3-30B-A3B has 32.

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