Model comparison

GLM-4.6 vs Granite 4.2 8B

GLM-4.6 and Granite 4.2 8B score almost the same on the Noometry Index (40.9 vs 40.0), so choose on price, context window or the category you care about most.

Last verified . 11 shared benchmarks.

GLM-4.6 Z.ai (Zhipu)

40.9

Rank #132 Confirmed

Granite 4.2 8B IBM

40.0

Rank #143 Confirmed

Summary

  • They share 11 benchmarks with published results for both. GLM-4.6 scores higher in 5 categories and Granite 4.2 8B in 2 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-4.6 leads 61.3 to 49.8.
  • Granite 4.2 8B is cheaper at $0.06 / $0.25 per million input/output tokens, against $0.60 / $2.20 for GLM-4.6.
  • GLM-4.6 accepts more context: 205K tokens versus 131K.

Side by side

GLM-4.6 and Granite 4.2 8B specifications
GLM-4.6Granite 4.2 8B
ProviderZ.ai (Zhipu)IBM
Noometry Index40.940.0
Released2025-09-30—
WeightsOpenOpen
Context window205K131K
Max output131K118K
Input $ / M tokens$0.60$0.06
Output $ / M tokens$2.20$0.25
Results tracked2911

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Category by category

Coding Too close to call

GLM-4.6: 39.9 (#137), Granite 4.2 8B: 39.9 (#138)

Coding benchmarks
BenchmarkGLM-4.6Granite 4.2 8B
LMArena Coding14491379
SWE-bench Verified (bash only)55.4%—
LMArena WebDev1339—
SciCode38.4%—
ALE-Bench340.82—

Agentic & Tool Use Not comparable

GLM-4.6: 32.1 (#60), Granite 4.2 8B: —

Agentic & Tool Use benchmarks
BenchmarkGLM-4.6Granite 4.2 8B
Terminal-Bench24.5%—
Berkeley Function Calling Leaderboard72.4%—

Reasoning Granite 4.2 8B leads

GLM-4.6: 23.1 (#168), Granite 4.2 8B: 25.5 (#130)

Reasoning benchmarks
BenchmarkGLM-4.6Granite 4.2 8B
LMArena Hard Prompts14401327
Kagi LLM Benchmark47.4%—
CritPt1.1%—

Math Not comparable

GLM-4.6: 36.4 (#115), Granite 4.2 8B: —

Math benchmarks
BenchmarkGLM-4.6Granite 4.2 8B
LMArena Math1431—
FrontierMath (Feb 2025 set)3.8%—
FrontierMath Tier 4 (v1)2.1%—

Knowledge GLM-4.6 leads

GLM-4.6: 39.6 (#118), Granite 4.2 8B: 37.7 (#144)

Knowledge benchmarks
BenchmarkGLM-4.6Granite 4.2 8B
LMArena Expert14321380
Vectara Hallucination Rate9.5%—

Multilingual GLM-4.6 leads

GLM-4.6: 53.6 (#62), Granite 4.2 8B: 44.5 (#173)

Multilingual benchmarks
BenchmarkGLM-4.6Granite 4.2 8B
LMArena Non-English14261299
LMArena Chinese15001361
LMArena Russian14181283
LMArena French1459—
LMArena German1447—
LMArena Japanese1394—
LMArena Korean1401—
LMArena Spanish1436—

Instruction Following GLM-4.6 leads

GLM-4.6: 74.5 (#93), Granite 4.2 8B: 68.7 (#183)

Instruction Following benchmarks
BenchmarkGLM-4.6Granite 4.2 8B
LMArena Instruction Following14101298

Long Context GLM-4.6 leads

GLM-4.6: 43.4 (#91), Granite 4.2 8B: 40.2 (#154)

Long Context benchmarks
BenchmarkGLM-4.6Granite 4.2 8B
LMArena Longer Query14231323

Writing & Preference GLM-4.6 leads

GLM-4.6: 61.3 (#86), Granite 4.2 8B: 49.8 (#183)

Writing & Preference benchmarks
BenchmarkGLM-4.6Granite 4.2 8B
LMArena Text14401319
LMArena Creative Writing14111238
LMArena Multi-Turn14271299
EQ-Bench Creative Writing1411—

Frequently asked questions

Is GLM-4.6 better than Granite 4.2 8B?

GLM-4.6 and Granite 4.2 8B score almost the same on the Noometry Index (40.9 vs 40.0), so choose on price, context window or the category you care about most.

Which is cheaper, GLM-4.6 or Granite 4.2 8B?

Granite 4.2 8B is cheaper. It lists at $0.06 per million input tokens and $0.25 per million output tokens; GLM-4.6 lists at $0.60 and $2.20.

Is GLM-4.6 or Granite 4.2 8B better for coding?

They score almost the same on coding (39.9 vs 39.9); test both on your own repository before choosing.

Which has the bigger context window?

GLM-4.6 does, with 205K tokens against 131K.

How many benchmarks do GLM-4.6 and Granite 4.2 8B share?

11 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Granite 4.2 8B has 11.

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