Noometry

Model comparison

GLM-4.6 vs Grok-2 (Dec 2024)

GLM-4.6 is the stronger model overall, scoring 40.9 to 33.4 on the Noometry Index.

Last verified . 18 shared benchmarks.

GLM-4.6 Z.ai (Zhipu)

40.9

Rank #132 Confirmed

Grok-2 (Dec 2024) xAI

33.4

Rank #233 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GLM-4.6 scores higher in 8 categories and Grok-2 (Dec 2024) in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-4.6 leads 36.4 to 19.6.
  • GLM-4.6 has downloadable open weights; the other is API-only.

Side by side

GLM-4.6Grok-2 (Dec 2024)
ProviderZ.ai (Zhipu)xAI
Noometry Index40.933.4
Released2025-09-302024-08-13
WeightsOpenProprietary
Context window205K—
Max output131K—
Input $ / M tokens$0.60—
Output $ / M tokens$2.20—
Results tracked2934

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Category by category

Coding GLM-4.6 leads

GLM-4.6: 39.9 (#137), Grok-2 (Dec 2024): 32.9 (#254)

BenchmarkGLM-4.6Grok-2 (Dec 2024)
LMArena Coding14491288
SWE-bench Verified (bash only)55.4%—
LMArena WebDev1339—
SciCode38.4%—
WeirdML—22.2%
LiveBench Coding—46.4%
ALE-Bench340.82—

Agentic & Tool Use Not comparable

GLM-4.6: 32.1 (#60), Grok-2 (Dec 2024): —

BenchmarkGLM-4.6Grok-2 (Dec 2024)
Terminal-Bench24.5%—
Berkeley Function Calling Leaderboard72.4%—

Reasoning GLM-4.6 leads

GLM-4.6: 23.1 (#168), Grok-2 (Dec 2024): 16.4 (#294)

BenchmarkGLM-4.6Grok-2 (Dec 2024)
LMArena Hard Prompts14401272
SimpleBench—22.7%
Kagi LLM Benchmark47.4%—
CritPt1.1%—
LiveBench Reasoning—54.8%
DTBench—65.2%
LiveBench Data Analysis—54.5%
Epoch Capabilities Index—130.48
LiveBench—54.3%

Math GLM-4.6 leads

GLM-4.6: 36.4 (#115), Grok-2 (Dec 2024): 19.6 (#278)

BenchmarkGLM-4.6Grok-2 (Dec 2024)
LMArena Math14311283
FrontierMath (Feb 2025 set)3.8%0.7%
OTIS Mock AIME 2024-2025—11.5%
LiveBench Math—54.9%
MATH Level 5—63.5%
FrontierMath Tier 4 (v1)2.1%—

Knowledge GLM-4.6 leads

GLM-4.6: 39.6 (#118), Grok-2 (Dec 2024): 29.8 (#225)

BenchmarkGLM-4.6Grok-2 (Dec 2024)
LMArena Expert14321254
GPQA Diamond—53.8%
Confabulations—20.1%
Vectara Hallucination Rate9.5%—

Multilingual GLM-4.6 leads

GLM-4.6: 53.6 (#62), Grok-2 (Dec 2024): 43.3 (#183)

BenchmarkGLM-4.6Grok-2 (Dec 2024)
LMArena Non-English14261282
LMArena Chinese15001289
LMArena French14591317
LMArena German14471287
LMArena Japanese13941244
LMArena Korean14011237
LMArena Russian14181286
LMArena Spanish14361281

Instruction Following GLM-4.6 leads

GLM-4.6: 74.5 (#93), Grok-2 (Dec 2024): 67.1 (#197)

BenchmarkGLM-4.6Grok-2 (Dec 2024)
LMArena Instruction Following14101270
LiveBench Instruction Following—69.6%

Long Context GLM-4.6 leads

GLM-4.6: 43.4 (#91), Grok-2 (Dec 2024): 38.7 (#186)

BenchmarkGLM-4.6Grok-2 (Dec 2024)
LMArena Longer Query14231276

Writing & Preference GLM-4.6 leads

GLM-4.6: 61.3 (#86), Grok-2 (Dec 2024): 48.8 (#192)

BenchmarkGLM-4.6Grok-2 (Dec 2024)
LMArena Text14401305
LMArena Creative Writing14111284
LMArena Multi-Turn14271290
Short-Story Creative Writing—63.6%
EQ-Bench Creative Writing1411—
LiveBench Language—45.6%

Frequently asked questions

Is GLM-4.6 better than Grok-2 (Dec 2024)?

GLM-4.6 is the stronger model overall, scoring 40.9 to 33.4 on the Noometry Index.

Is GLM-4.6 or Grok-2 (Dec 2024) better for coding?

GLM-4.6 scores higher on coding benchmarks: 39.9 versus 32.9 in the Noometry coding category.

How many benchmarks do GLM-4.6 and Grok-2 (Dec 2024) share?

18 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Grok-2 (Dec 2024) has 34.

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