Model comparison

GLM-4.7 vs Step 2 16k Exp 202412

GLM-4.7 is the stronger model overall, scoring 41.7 to 38.6 on the Noometry Index.

Last verified . 12 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

41.7

Rank #117 Confirmed

Step 2 16k Exp 202412 StepFun

38.6

Rank #173 Confirmed

Summary

  • They share 12 benchmarks with published results for both. GLM-4.7 scores higher in 7 categories and Step 2 16k Exp 202412 in 1 category; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.7 leads 47.0 to 34.6.
  • GLM-4.7 has downloadable open weights; the other is API-only.

Side by side

GLM-4.7 and Step 2 16k Exp 202412 specifications
GLM-4.7Step 2 16k Exp 202412
ProviderZ.ai (Zhipu)StepFun
Noometry Index41.738.6
Released2025-12-22—
WeightsOpenProprietary
Context window205K—
Max output131K—
Input $ / M tokens$0.60—
Output $ / M tokens$2.20—
Results tracked3612

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Category by category

Coding GLM-4.7 leads

GLM-4.7: 43.6 (#74), Step 2 16k Exp 202412: 37.9 (#170)

Coding benchmarks
BenchmarkGLM-4.7Step 2 16k Exp 202412
LMArena Coding14541316
LMArena WebDev1435—
SciCode45.1%—
ALE-Bench399.48—

Agentic & Tool Use Not comparable

GLM-4.7: 26.4 (#96), Step 2 16k Exp 202412: —

Agentic & Tool Use benchmarks
BenchmarkGLM-4.7Step 2 16k Exp 202412
Terminal-Bench33.4%—
Vending-Bench 22,377—

Reasoning Step 2 16k Exp 202412 leads

GLM-4.7: 23.7 (#161), Step 2 16k Exp 202412: 24.8 (#140)

Reasoning benchmarks
BenchmarkGLM-4.7Step 2 16k Exp 202412
LMArena Hard Prompts14431299
SimpleBench47.7%—
CritPt1.7%—
Chess Puzzles6%—
Epoch Capabilities Index143.53—

Math GLM-4.7 leads

GLM-4.7: 37.7 (#92), Step 2 16k Exp 202412: 33.6 (#171)

Math benchmarks
BenchmarkGLM-4.7Step 2 16k Exp 202412
LMArena Math14231305
OTIS Mock AIME 2024-202583.3%—
ProofBench6%—
FrontierMath (Feb 2025 set)2.4%—
FrontierMath Tier 4 (v1)0%—

Knowledge GLM-4.7 leads

GLM-4.7: 47.0 (#74), Step 2 16k Exp 202412: 34.6 (#187)

Knowledge benchmarks
BenchmarkGLM-4.7Step 2 16k Exp 202412
LMArena Expert14241279
GPQA Diamond83.3%—
SimpleQA Verified32.2%—
Vectara Hallucination Rate11.7%—

Multilingual GLM-4.7 leads

GLM-4.7: 53.0 (#75), Step 2 16k Exp 202412: 43.9 (#176)

Multilingual benchmarks
BenchmarkGLM-4.7Step 2 16k Exp 202412
LMArena Non-English14171290
LMArena Chinese14951331
LMArena Russian14231324
LMArena French1432—
LMArena German1426—
LMArena Japanese1439—
LMArena Korean1401—
LMArena Spanish1433—

Instruction Following GLM-4.7 leads

GLM-4.7: 74.6 (#90), Step 2 16k Exp 202412: 68.1 (#187)

Instruction Following benchmarks
BenchmarkGLM-4.7Step 2 16k Exp 202412
LMArena Instruction Following14111287

Long Context GLM-4.7 leads

GLM-4.7: 42.8 (#111), Step 2 16k Exp 202412: 39.7 (#165)

Long Context benchmarks
BenchmarkGLM-4.7Step 2 16k Exp 202412
LMArena Longer Query14321307
CL-bench15.9%—
CL-bench Life10.9%—

Writing & Preference GLM-4.7 leads

GLM-4.7: 61.1 (#89), Step 2 16k Exp 202412: 52.5 (#168)

Writing & Preference benchmarks
BenchmarkGLM-4.7Step 2 16k Exp 202412
LMArena Text14361321
LMArena Creative Writing14011328
LMArena Multi-Turn14461292
EQ-Bench Creative Writing1413—

Frequently asked questions

Is GLM-4.7 better than Step 2 16k Exp 202412?

GLM-4.7 is the stronger model overall, scoring 41.7 to 38.6 on the Noometry Index.

Is GLM-4.7 or Step 2 16k Exp 202412 better for coding?

GLM-4.7 scores higher on coding benchmarks: 43.6 versus 37.9 in the Noometry coding category.

How many benchmarks do GLM-4.7 and Step 2 16k Exp 202412 share?

12 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Step 2 16k Exp 202412 has 12.

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