Noometry

Model comparison

GLM-4.7-Flash vs Granite 4.0 Micro

GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 29.0 on the Noometry Index. Granite 4.0 Micro costs 3.6× less per token, which makes it the better buy when GLM-4.7-Flash's lead doesn't matter for your workload.

Last verified . 3 shared benchmarks.

GLM-4.7-Flash Z.ai (Zhipu)

38.8

Rank #180 Confirmed

Granite 4.0 Micro IBM

29.0

Rank #318 Confirmed

Summary

  • They share 3 benchmarks with published results for both. GLM-4.7-Flash scores higher in 5 categories and Granite 4.0 Micro in 0 categories; 3 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.7-Flash leads 35.5 to 9.9.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 58.3% for GLM-4.7-Flash and 2.8% for Granite 4.0 Micro.
  • Granite 4.0 Micro is cheaper at $0.017 / $0.11 per million input/output tokens, against $0.06 / $0.40 for GLM-4.7-Flash.
  • GLM-4.7-Flash accepts more context: 200K tokens versus 131K.

Side by side

GLM-4.7-FlashGranite 4.0 Micro
ProviderZ.ai (Zhipu)IBM
Noometry Index38.829.0
Released2026-01-192025-10-02
WeightsOpenOpen
Context window200K131K
Max output131K118K
Input $ / M tokens$0.06$0.017
Output $ / M tokens$0.40$0.11
Results tracked218

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Category by category

Coding Not comparable

GLM-4.7-Flash: 40.6 (#135), Granite 4.0 Micro: —

BenchmarkGLM-4.7-FlashGranite 4.0 Micro
LMArena Coding1383—

Reasoning GLM-4.7-Flash leads

GLM-4.7-Flash: 20.9 (#229), Granite 4.0 Micro: 19.2 (#265)

BenchmarkGLM-4.7-FlashGranite 4.0 Micro
Chess Puzzles0%0%
LMArena Hard Prompts1356—

Math GLM-4.7-Flash leads

GLM-4.7-Flash: 36.1 (#173), Granite 4.0 Micro: 12.0 (#307)

BenchmarkGLM-4.7-FlashGranite 4.0 Micro
OTIS Mock AIME 2024-202558.3%2.8%
Omni-MATH—20.9%
LMArena Math1355—

Knowledge GLM-4.7-Flash leads

GLM-4.7-Flash: 35.5 (#184), Granite 4.0 Micro: 9.9 (#304)

BenchmarkGLM-4.7-FlashGranite 4.0 Micro
GPQA Diamond60.5%28.3%
MMLU-Pro—39.5%
Vectara Hallucination Rate9.3%—
GPQA (HELM)—30.7%
LMArena Expert1357—

Multilingual Not comparable

GLM-4.7-Flash: 46.5 (#158), Granite 4.0 Micro: —

BenchmarkGLM-4.7-FlashGranite 4.0 Micro
LMArena Non-English1330—
LMArena Chinese1403—
LMArena French1332—
LMArena German1337—
LMArena Korean1283—
LMArena Russian1332—
LMArena Spanish1350—

Instruction Following Too close to call

GLM-4.7-Flash: 70.1 (#167), Granite 4.0 Micro: 69.9 (#169)

BenchmarkGLM-4.7-FlashGranite 4.0 Micro
IFEval—84.9%
LMArena Instruction Following1327—

Long Context Not comparable

GLM-4.7-Flash: 40.9 (#148), Granite 4.0 Micro: —

BenchmarkGLM-4.7-FlashGranite 4.0 Micro
LMArena Longer Query1345—

Writing & Preference Too close to call

GLM-4.7-Flash: 47.4 (#210), Granite 4.0 Micro: 46.7 (#216)

BenchmarkGLM-4.7-FlashGranite 4.0 Micro
LMArena Text1351—
LMArena Creative Writing1297—
EQ-Bench Creative Writing1125—
WildBench—67%
LMArena Multi-Turn1342—

Frequently asked questions

Is GLM-4.7-Flash better than Granite 4.0 Micro?

GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 29.0 on the Noometry Index. Granite 4.0 Micro costs 3.6× less per token, which makes it the better buy when GLM-4.7-Flash's lead doesn't matter for your workload.

Which is cheaper, GLM-4.7-Flash or Granite 4.0 Micro?

Granite 4.0 Micro is cheaper. It lists at $0.017 per million input tokens and $0.11 per million output tokens; GLM-4.7-Flash lists at $0.06 and $0.40.

Which has the bigger context window?

GLM-4.7-Flash does, with 200K tokens against 131K.

How many benchmarks do GLM-4.7-Flash and Granite 4.0 Micro share?

3 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Granite 4.0 Micro has 8.

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