Noometry

Model comparison

GLM-4.6 vs GLM-5V-Turbo

GLM-5V-Turbo is the stronger model overall, scoring 43.8 to 41.4 on the Noometry Index. GLM-4.6 costs 1.9× less per token, which makes it the better buy when GLM-5V-Turbo's lead doesn't matter for your workload.

Last verified . 17 shared benchmarks.

GLM-4.6 Z.ai (Zhipu)

41.4

Rank #135 Confirmed

GLM-5V-Turbo Z.ai (Zhipu)

43.8

Rank #84 Confirmed

Summary

  • They share 17 benchmarks with published results for both. GLM-4.6 scores higher in 1 category and GLM-5V-Turbo in 7 categories; 3 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-5V-Turbo leads 29.7 to 23.7.
  • GLM-4.6 is cheaper at $0.60 / $2.20 per million input/output tokens, against $1.20 / $4 for GLM-5V-Turbo.
  • GLM-4.6 accepts more context: 205K tokens versus 200K.
  • GLM-4.6 has downloadable open weights; the other is API-only.

Side by side

GLM-4.6GLM-5V-Turbo
ProviderZ.ai (Zhipu)Z.ai (Zhipu)
Noometry Index41.443.8
Released2025-09-302026-04-01
WeightsOpenProprietary
Context window205K200K
Max output131K131K
Input $ / M tokens$0.60$1.20
Output $ / M tokens$2.20$4
Results tracked2919

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Category by category

Coding GLM-5V-Turbo leads

GLM-4.6: 40.1 (#148), GLM-5V-Turbo: 42.1 (#111)

BenchmarkGLM-4.6GLM-5V-Turbo
LMArena WebDev13401401
LMArena Coding14491466
SWE-bench Verified (bash only)55.4%—
SciCode38.4%—
ALE-Bench340.82—

Agentic & Tool Use Not comparable

GLM-4.6: 32.3 (#66), GLM-5V-Turbo: —

BenchmarkGLM-4.6GLM-5V-Turbo
Terminal-Bench24.5%—
Berkeley Function Calling Leaderboard72.4%—

Reasoning GLM-5V-Turbo leads

GLM-4.6: 23.7 (#172), GLM-5V-Turbo: 29.7 (#89)

BenchmarkGLM-4.6GLM-5V-Turbo
LMArena Hard Prompts14401443
Kagi LLM Benchmark47.4%—
CritPt1.1%—

Math Too close to call

GLM-4.6: 39.1 (#111), GLM-5V-Turbo: 39.4 (#106)

BenchmarkGLM-4.6GLM-5V-Turbo
LMArena Math14321441
FrontierMath (Feb 2025 set)3.8%—
FrontierMath Tier 4 (v1)2.1%—

Knowledge Too close to call

GLM-4.6: 40.2 (#124), GLM-5V-Turbo: 40.6 (#117)

BenchmarkGLM-4.6GLM-5V-Turbo
LMArena Expert14311452
Vectara Hallucination Rate9.5%—

Multimodal Not comparable

GLM-4.6: —, GLM-5V-Turbo: 40.9 (#42)

BenchmarkGLM-4.6GLM-5V-Turbo
LMArena Vision—1264
LMArena Document—1416

Multilingual Too close to call

GLM-4.6: 53.5 (#66), GLM-5V-Turbo: 53.0 (#73)

BenchmarkGLM-4.6GLM-5V-Turbo
LMArena Non-English14261420
LMArena Chinese14991488
LMArena French14591444
LMArena German14471423
LMArena Korean14001396
LMArena Russian14191431
LMArena Spanish14361450
LMArena Japanese1393—

Instruction Following Too close to call

GLM-4.6: 74.3 (#98), GLM-5V-Turbo: 75.0 (#80)

BenchmarkGLM-4.6GLM-5V-Turbo
LMArena Instruction Following14101423

Long Context Too close to call

GLM-4.6: 43.4 (#94), GLM-5V-Turbo: 44.0 (#80)

BenchmarkGLM-4.6GLM-5V-Turbo
LMArena Longer Query14221438

Writing & Preference GLM-5V-Turbo leads

GLM-4.6: 61.1 (#90), GLM-5V-Turbo: 62.5 (#73)

BenchmarkGLM-4.6GLM-5V-Turbo
LMArena Text14401437
LMArena Creative Writing14111416
LMArena Multi-Turn14271432
EQ-Bench Creative Writing1411—

Frequently asked questions

Is GLM-4.6 better than GLM-5V-Turbo?

GLM-5V-Turbo is the stronger model overall, scoring 43.8 to 41.4 on the Noometry Index. GLM-4.6 costs 1.9× less per token, which makes it the better buy when GLM-5V-Turbo's lead doesn't matter for your workload.

Which is cheaper, GLM-4.6 or GLM-5V-Turbo?

GLM-4.6 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; GLM-5V-Turbo lists at $1.20 and $4.

Is GLM-4.6 or GLM-5V-Turbo better for coding?

GLM-5V-Turbo scores higher on coding benchmarks: 42.1 versus 40.1 in the Noometry coding category.

Which has the bigger context window?

GLM-4.6 does, with 205K tokens against 200K.

How many benchmarks do GLM-4.6 and GLM-5V-Turbo share?

17 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and GLM-5V-Turbo has 19.

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