Noometry

Model comparison

GLM-4.5 vs GLM-4.7

GLM-4.5 and GLM-4.7 score almost the same on the Noometry Index (42.0 vs 42.0), so choose on price, context window or the category you care about most.

Last verified . 19 shared benchmarks.

GLM-4.5 Z.ai (Zhipu)

42.0

Rank #122 Confirmed

GLM-4.7 Z.ai (Zhipu)

42.0

Rank #124 Confirmed

Summary

  • They share 19 benchmarks with published results for both. GLM-4.5 scores higher in 3 categories and GLM-4.7 in 5 categories; 5 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.7 leads 47.0 to 35.9.
  • Both cost about the same: $0.60 input and $2.20 output per million tokens.
  • GLM-4.7 accepts more context: 205K tokens versus 131K.

Side by side

GLM-4.5GLM-4.7
ProviderZ.ai (Zhipu)Z.ai (Zhipu)
Noometry Index42.042.0
Released2025-07-272025-12-22
WeightsOpenOpen
Context window131K205K
Max output98K131K
Input $ / M tokens$0.60$0.60
Output $ / M tokens$2.20$2.20
Results tracked2736

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Category by category

Coding GLM-4.7 leads

GLM-4.5: 41.4 (#125), GLM-4.7: 44.0 (#79)

BenchmarkGLM-4.5GLM-4.7
LMArena Coding14341454
ALE-Bench344.82399.48
SWE-bench Verified (bash only)54.2%—
LMArena WebDev—1435
SciCode—45.1%
WeirdML40.6%—
AlgoTune1.52—

Agentic & Tool Use Not comparable

GLM-4.5: —, GLM-4.7: 26.5 (#103)

BenchmarkGLM-4.5GLM-4.7
Terminal-Bench—33.4%
Vending-Bench 2—2,377

Reasoning GLM-4.5 leads

GLM-4.5: 28.6 (#100), GLM-4.7: 24.3 (#164)

BenchmarkGLM-4.5GLM-4.7
LMArena Hard Prompts14291443
SimpleBench—47.7%
Kagi LLM Benchmark57.9%—
CritPt—1.7%
Chess Puzzles—6%
Epoch Capabilities Index—143.51

Math Too close to call

GLM-4.5: 39.0 (#116), GLM-4.7: 38.6 (#135)

BenchmarkGLM-4.5GLM-4.7
LMArena Math14271423
OTIS Mock AIME 2024-2025—83.3%
ProofBench—6%
FrontierMath (Feb 2025 set)—2.4%
FrontierMath Tier 4 (v1)—0%

Knowledge GLM-4.7 leads

GLM-4.5: 35.9 (#179), GLM-4.7: 47.0 (#80)

BenchmarkGLM-4.5GLM-4.7
LMArena Expert14331424
GPQA Diamond—83.3%
Humanity's Last Exam8.3%—
SimpleQA Verified—32.2%
Confabulations11.3%—
Vectara Hallucination Rate—11.7%

Multilingual Too close to call

GLM-4.5: 52.8 (#77), GLM-4.7: 52.8 (#79)

BenchmarkGLM-4.5GLM-4.7
LMArena Non-English14171417
LMArena Chinese14651495
LMArena French14181432
LMArena German14071424
LMArena Japanese14151439
LMArena Korean13801399
LMArena Russian14141423
LMArena Spanish14541434

Instruction Following Too close to call

GLM-4.5: 74.1 (#104), GLM-4.7: 74.4 (#95)

BenchmarkGLM-4.5GLM-4.7
LMArena Instruction Following14041411

Long Context GLM-4.7 leads

GLM-4.5: 38.2 (#201), GLM-4.7: 42.8 (#116)

BenchmarkGLM-4.5GLM-4.7
LMArena Longer Query14121432
Fiction.LiveBench58.3%—
CL-bench—15.9%
CL-bench Life—10.9%

Writing & Preference GLM-4.7 leads

GLM-4.5: 57.5 (#127), GLM-4.7: 60.9 (#93)

BenchmarkGLM-4.5GLM-4.7
LMArena Text14301435
LMArena Creative Writing13951401
EQ-Bench Creative Writing13431413
LMArena Multi-Turn14151446
Short-Story Creative Writing73.4%—

Frequently asked questions

Is GLM-4.5 better than GLM-4.7?

GLM-4.5 and GLM-4.7 score almost the same on the Noometry Index (42.0 vs 42.0), so choose on price, context window or the category you care about most.

Which is cheaper, GLM-4.5 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-4.5 lists at $0.60 and $2.20.

Is GLM-4.5 or GLM-4.7 better for coding?

GLM-4.7 scores higher on coding benchmarks: 44.0 versus 41.4 in the Noometry coding category.

Which has the bigger context window?

GLM-4.7 does, with 205K tokens against 131K.

How many benchmarks do GLM-4.5 and GLM-4.7 share?

19 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and GLM-4.7 has 36.

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