Noometry

Model comparison

GLM-4.5 vs GLM-4.6

GLM-4.5 and GLM-4.6 score almost the same on the Noometry Index (42.0 vs 41.4), so choose on price, context window or the category you care about most.

Last verified . 21 shared benchmarks.

GLM-4.5 Z.ai (Zhipu)

42.0

Rank #122 Confirmed

GLM-4.6 Z.ai (Zhipu)

41.4

Rank #135 Confirmed

Summary

  • They share 21 benchmarks with published results for both. GLM-4.5 scores higher in 2 categories and GLM-4.6 in 6 categories; 5 gaps are clear of the uncertainty.
  • The widest gap is in long context, where GLM-4.6 leads 43.4 to 38.2.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 57.9% for GLM-4.5 and 47.4% for GLM-4.6.
  • Both cost about the same: $0.60 input and $2.20 output per million tokens.
  • GLM-4.6 accepts more context: 205K tokens versus 131K.

Side by side

GLM-4.5GLM-4.6
ProviderZ.ai (Zhipu)Z.ai (Zhipu)
Noometry Index42.041.4
Released2025-07-272025-09-30
WeightsOpenOpen
Context window131K205K
Max output98K131K
Input $ / M tokens$0.60$0.60
Output $ / M tokens$2.20$2.20
Results tracked2729

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Category by category

Coding GLM-4.5 leads

GLM-4.5: 41.4 (#125), GLM-4.6: 40.1 (#148)

BenchmarkGLM-4.5GLM-4.6
SWE-bench Verified (bash only)54.2%55.4%
LMArena Coding14341449
ALE-Bench344.82340.82
LMArena WebDev—1340
SciCode—38.4%
WeirdML40.6%—
AlgoTune1.52—

Agentic & Tool Use Not comparable

GLM-4.5: —, GLM-4.6: 32.3 (#66)

BenchmarkGLM-4.5GLM-4.6
Terminal-Bench—24.5%
Berkeley Function Calling Leaderboard—72.4%

Reasoning GLM-4.5 leads

GLM-4.5: 28.6 (#100), GLM-4.6: 23.7 (#172)

BenchmarkGLM-4.5GLM-4.6
Kagi LLM Benchmark57.9%47.4%
LMArena Hard Prompts14291440
CritPt—1.1%

Math Too close to call

GLM-4.5: 39.0 (#116), GLM-4.6: 39.1 (#111)

BenchmarkGLM-4.5GLM-4.6
LMArena Math14271432
FrontierMath (Feb 2025 set)—3.8%
FrontierMath Tier 4 (v1)—2.1%

Knowledge GLM-4.6 leads

GLM-4.5: 35.9 (#179), GLM-4.6: 40.2 (#124)

BenchmarkGLM-4.5GLM-4.6
LMArena Expert14331431
Humanity's Last Exam8.3%—
Confabulations11.3%—
Vectara Hallucination Rate—9.5%

Multilingual Too close to call

GLM-4.5: 52.8 (#77), GLM-4.6: 53.5 (#66)

BenchmarkGLM-4.5GLM-4.6
LMArena Non-English14171426
LMArena Chinese14651499
LMArena French14181459
LMArena German14071447
LMArena Japanese14151393
LMArena Korean13801400
LMArena Russian14141419
LMArena Spanish14541436

Instruction Following Too close to call

GLM-4.5: 74.1 (#104), GLM-4.6: 74.3 (#98)

BenchmarkGLM-4.5GLM-4.6
LMArena Instruction Following14041410

Long Context GLM-4.6 leads

GLM-4.5: 38.2 (#201), GLM-4.6: 43.4 (#94)

BenchmarkGLM-4.5GLM-4.6
LMArena Longer Query14121422
Fiction.LiveBench58.3%—

Writing & Preference GLM-4.6 leads

GLM-4.5: 57.5 (#127), GLM-4.6: 61.1 (#90)

BenchmarkGLM-4.5GLM-4.6
LMArena Text14301440
LMArena Creative Writing13951411
EQ-Bench Creative Writing13431411
LMArena Multi-Turn14151427
Short-Story Creative Writing73.4%—

Frequently asked questions

Is GLM-4.5 better than GLM-4.6?

GLM-4.5 and GLM-4.6 score almost the same on the Noometry Index (42.0 vs 41.4), so choose on price, context window or the category you care about most.

Which is cheaper, GLM-4.5 or GLM-4.6?

GLM-4.6 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; GLM-4.5 lists at $0.60 and $2.20.

Is GLM-4.5 or GLM-4.6 better for coding?

GLM-4.5 scores higher on coding benchmarks: 41.4 versus 40.1 in the Noometry coding category.

Which has the bigger context window?

GLM-4.6 does, with 205K tokens against 131K.

How many benchmarks do GLM-4.5 and GLM-4.6 share?

21 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and GLM-4.6 has 29.

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