Noometry

Model comparison

GLM-4.6 vs GLM-4.7

GLM-4.6 and GLM-4.7 score almost the same on the Noometry Index (41.4 vs 42.0), so choose on price, context window or the category you care about most.

Last verified . 26 shared benchmarks.

GLM-4.6 Z.ai (Zhipu)

41.4

Rank #135 Confirmed

GLM-4.7 Z.ai (Zhipu)

42.0

Rank #124 Confirmed

Summary

  • They share 26 benchmarks with published results for both. GLM-4.6 scores higher in 5 categories and GLM-4.7 in 4 categories; 3 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.7 leads 47.0 to 40.2.
  • The biggest single-benchmark swing is Terminal-Bench: 24.5% for GLM-4.6 and 33.4% for GLM-4.7.
  • Both cost about the same: $0.60 input and $2.20 output per million tokens.

Side by side

GLM-4.6GLM-4.7
ProviderZ.ai (Zhipu)Z.ai (Zhipu)
Noometry Index41.442.0
Released2025-09-302025-12-22
WeightsOpenOpen
Context window205K205K
Max output131K131K
Input $ / M tokens$0.60$0.60
Output $ / M tokens$2.20$2.20
Results tracked2936

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Category by category

Coding GLM-4.7 leads

GLM-4.6: 40.1 (#148), GLM-4.7: 44.0 (#79)

BenchmarkGLM-4.6GLM-4.7
LMArena WebDev13401435
SciCode38.4%45.1%
LMArena Coding14491454
ALE-Bench340.82399.48
SWE-bench Verified (bash only)55.4%—

Agentic & Tool Use GLM-4.6 leads

GLM-4.6: 32.3 (#66), GLM-4.7: 26.5 (#103)

BenchmarkGLM-4.6GLM-4.7
Terminal-Bench24.5%33.4%
Berkeley Function Calling Leaderboard72.4%—
Vending-Bench 2—2,377

Reasoning Too close to call

GLM-4.6: 23.7 (#172), GLM-4.7: 24.3 (#164)

BenchmarkGLM-4.6GLM-4.7
CritPt1.1%1.7%
LMArena Hard Prompts14401443
SimpleBench—47.7%
Kagi LLM Benchmark47.4%—
Chess Puzzles—6%
Epoch Capabilities Index—143.51

Math Too close to call

GLM-4.6: 39.1 (#111), GLM-4.7: 38.6 (#135)

BenchmarkGLM-4.6GLM-4.7
LMArena Math14321423
FrontierMath (Feb 2025 set)3.8%2.4%
FrontierMath Tier 4 (v1)2.1%0%
OTIS Mock AIME 2024-2025—83.3%
ProofBench—6%

Knowledge GLM-4.7 leads

GLM-4.6: 40.2 (#124), GLM-4.7: 47.0 (#80)

BenchmarkGLM-4.6GLM-4.7
Vectara Hallucination Rate9.5%11.7%
LMArena Expert14311424
GPQA Diamond—83.3%
SimpleQA Verified—32.2%

Multilingual Too close to call

GLM-4.6: 53.5 (#66), GLM-4.7: 52.8 (#79)

BenchmarkGLM-4.6GLM-4.7
LMArena Non-English14261417
LMArena Chinese14991495
LMArena French14591432
LMArena German14471424
LMArena Japanese13931439
LMArena Korean14001399
LMArena Russian14191423
LMArena Spanish14361434

Instruction Following Too close to call

GLM-4.6: 74.3 (#98), GLM-4.7: 74.4 (#95)

BenchmarkGLM-4.6GLM-4.7
LMArena Instruction Following14101411

Long Context Too close to call

GLM-4.6: 43.4 (#94), GLM-4.7: 42.8 (#116)

BenchmarkGLM-4.6GLM-4.7
LMArena Longer Query14221432
CL-bench—15.9%
CL-bench Life—10.9%

Writing & Preference Too close to call

GLM-4.6: 61.1 (#90), GLM-4.7: 60.9 (#93)

BenchmarkGLM-4.6GLM-4.7
LMArena Text14401435
LMArena Creative Writing14111401
EQ-Bench Creative Writing14111413
LMArena Multi-Turn14271446

Frequently asked questions

Is GLM-4.6 better than GLM-4.7?

GLM-4.6 and GLM-4.7 score almost the same on the Noometry Index (41.4 vs 42.0), so choose on price, context window or the category you care about most.

Which is cheaper, GLM-4.6 or GLM-4.7?

GLM-4.7 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; GLM-4.6 lists at $0.60 and $2.20.

Is GLM-4.6 or GLM-4.7 better for coding?

GLM-4.7 scores higher on coding benchmarks: 44.0 versus 40.1 in the Noometry coding category.

Which has the bigger context window?

Both accept 205K tokens.

How many benchmarks do GLM-4.6 and GLM-4.7 share?

26 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and GLM-4.7 has 36.

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