Noometry

Model comparison

GLM-4.7 vs Grok 3

GLM-4.7 is the stronger model overall, scoring 42.0 to 39.9 on the Noometry Index.

Last verified . 25 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

42.0

Rank #124 Confirmed

Grok 3 xAI

39.9

Rank #157 Confirmed

Summary

  • They share 25 benchmarks with published results for both. GLM-4.7 scores higher in 7 categories and Grok 3 in 2 categories; 5 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-4.7 leads 24.3 to 13.7.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 83.3% for GLM-4.7 and 55.6% for Grok 3.
  • GLM-4.7 has downloadable open weights; the other is API-only.

Side by side

GLM-4.7Grok 3
ProviderZ.ai (Zhipu)xAI
Noometry Index42.039.9
Released2025-12-222025-04-09
WeightsOpenProprietary
Context window205K—
Max output131K—
Input $ / M tokens$0.60—
Output $ / M tokens$2.20—
Results tracked3640

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Category by category

Coding GLM-4.7 leads

GLM-4.7: 44.0 (#79), Grok 3: 41.9 (#115)

BenchmarkGLM-4.7Grok 3
LMArena Coding14541432
Aider Polyglot—53.3%
LMArena WebDev1435—
SciCode45.1%—
WeirdML—37.2%
ALE-Bench399.48—

Agentic & Tool Use Grok 3 leads

GLM-4.7: 26.5 (#103), Grok 3: 30.5 (#76)

BenchmarkGLM-4.7Grok 3
Terminal-Bench33.4%—
BALROG—29.5%
Vending-Bench 22,377—

Reasoning GLM-4.7 leads

GLM-4.7: 24.3 (#164), Grok 3: 13.7 (#333)

BenchmarkGLM-4.7Grok 3
SimpleBench47.7%36.1%
LMArena Hard Prompts14431434
Epoch Capabilities Index143.51138.33
ARC-AGI-2—0%
Kagi LLM Benchmark—61.3%
ARC-AGI-1—5.5%
CritPt1.7%—
Chess Puzzles6%—

Math Too close to call

GLM-4.7: 38.6 (#135), Grok 3: 38.0 (#145)

BenchmarkGLM-4.7Grok 3
OTIS Mock AIME 2024-202583.3%55.6%
LMArena Math14231391
FrontierMath (Feb 2025 set)2.4%3.8%
FrontierMath Tier 4 (v1)0%0%
ProofBench6%—
Omni-MATH—46.4%
MATH Level 5—88.7%

Knowledge Too close to call

GLM-4.7: 47.0 (#80), Grok 3: 46.2 (#82)

BenchmarkGLM-4.7Grok 3
GPQA Diamond83.3%75.8%
Vectara Hallucination Rate11.7%5.8%
LMArena Expert14241421
SimpleQA Verified32.2%—
MMLU-Pro—78.8%
Confabulations—14.2%
GPQA (HELM)—65%

Multilingual Too close to call

GLM-4.7: 52.8 (#79), Grok 3: 52.3 (#87)

BenchmarkGLM-4.7Grok 3
LMArena Non-English14171410
LMArena Chinese14951448
LMArena French14321460
LMArena German14241431
LMArena Japanese14391387
LMArena Korean13991373
LMArena Russian14231416
LMArena Spanish14341417

Instruction Following Too close to call

GLM-4.7: 74.4 (#95), Grok 3: 75.0 (#73)

BenchmarkGLM-4.7Grok 3
LMArena Instruction Following14111409
IFEval—88.4%

Long Context GLM-4.7 leads

GLM-4.7: 42.8 (#116), Grok 3: 38.7 (#192)

BenchmarkGLM-4.7Grok 3
LMArena Longer Query14321439
Fiction.LiveBench—58.3%
CL-bench15.9%—
CL-bench Life10.9%—

Writing & Preference GLM-4.7 leads

GLM-4.7: 60.9 (#93), Grok 3: 55.8 (#141)

BenchmarkGLM-4.7Grok 3
LMArena Text14351426
LMArena Creative Writing14011414
EQ-Bench Creative Writing14131186
LMArena Multi-Turn14461425
Short-Story Creative Writing—76.4%
WildBench—84.9%

Frequently asked questions

Is GLM-4.7 better than Grok 3?

GLM-4.7 is the stronger model overall, scoring 42.0 to 39.9 on the Noometry Index.

Is GLM-4.7 or Grok 3 better for coding?

GLM-4.7 scores higher on coding benchmarks: 44.0 versus 41.9 in the Noometry coding category.

How many benchmarks do GLM-4.7 and Grok 3 share?

25 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Grok 3 has 40.

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