Noometry

Model comparison

GLM-4.6 vs Ministral 8B

GLM-4.6 is the stronger model overall, scoring 41.4 to 28.2 on the Noometry Index. Ministral 8B costs 6.7× less per token, which makes it the better buy when GLM-4.6's lead doesn't matter for your workload.

Last verified . 14 shared benchmarks.

GLM-4.6 Z.ai (Zhipu)

41.4

Rank #135 Confirmed

Ministral 8B Mistral AI

28.2

Rank #325 Confirmed

Summary

  • They share 14 benchmarks with published results for both. GLM-4.6 scores higher in 9 categories and Ministral 8B in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.6 leads 40.2 to 12.6.
  • The biggest single-benchmark swing is Berkeley Function Calling Leaderboard: 72.4% for GLM-4.6 and 11.1% for Ministral 8B.
  • Ministral 8B is cheaper at $0.15 / $0.15 per million input/output tokens, against $0.60 / $2.20 for GLM-4.6.
  • Ministral 8B accepts more context: 262K tokens versus 205K.

Side by side

GLM-4.6Ministral 8B
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index41.428.2
Released2025-09-302024-10-01
WeightsOpenOpen
Context window205K262K
Max output131K262K
Input $ / M tokens$0.60$0.15
Output $ / M tokens$2.20$0.15
Results tracked2917

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Category by category

Coding GLM-4.6 leads

GLM-4.6: 40.1 (#148), Ministral 8B: 35.0 (#230)

BenchmarkGLM-4.6Ministral 8B
LMArena Coding14491202
SWE-bench Verified (bash only)55.4%—
LMArena WebDev1340—
SciCode38.4%—
ALE-Bench340.82—

Agentic & Tool Use GLM-4.6 leads

GLM-4.6: 32.3 (#66), Ministral 8B: 16.4 (#148)

BenchmarkGLM-4.6Ministral 8B
Berkeley Function Calling Leaderboard72.4%11.1%
Terminal-Bench24.5%—

Reasoning GLM-4.6 leads

GLM-4.6: 23.7 (#172), Ministral 8B: 18.4 (#281)

BenchmarkGLM-4.6Ministral 8B
LMArena Hard Prompts14401191
Kagi LLM Benchmark47.4%—
CritPt1.1%—
DTBench—45.7%

Math GLM-4.6 leads

GLM-4.6: 39.1 (#111), Ministral 8B: 25.7 (#267)

BenchmarkGLM-4.6Ministral 8B
LMArena Math14321188
MATH Level 5—14.9%
FrontierMath (Feb 2025 set)3.8%—
FrontierMath Tier 4 (v1)2.1%—

Knowledge GLM-4.6 leads

GLM-4.6: 40.2 (#124), Ministral 8B: 12.6 (#297)

BenchmarkGLM-4.6Ministral 8B
Vectara Hallucination Rate9.5%7.4%
LMArena Expert14311170
GPQA Diamond—27.1%

Multilingual GLM-4.6 leads

GLM-4.6: 53.5 (#66), Ministral 8B: 35.1 (#247)

BenchmarkGLM-4.6Ministral 8B
LMArena Non-English14261165
LMArena Chinese14991193
LMArena Russian14191195
LMArena French1459—
LMArena German1447—
LMArena Japanese1393—
LMArena Korean1400—
LMArena Spanish1436—

Instruction Following GLM-4.6 leads

GLM-4.6: 74.3 (#98), Ministral 8B: 60.5 (#250)

BenchmarkGLM-4.6Ministral 8B
LMArena Instruction Following14101161

Long Context GLM-4.6 leads

GLM-4.6: 43.4 (#94), Ministral 8B: 36.7 (#227)

BenchmarkGLM-4.6Ministral 8B
LMArena Longer Query14221212

Writing & Preference GLM-4.6 leads

GLM-4.6: 61.1 (#90), Ministral 8B: 39.6 (#246)

BenchmarkGLM-4.6Ministral 8B
LMArena Text14401191
LMArena Creative Writing14111175
LMArena Multi-Turn14271166
EQ-Bench Creative Writing1411—

Frequently asked questions

Is GLM-4.6 better than Ministral 8B?

GLM-4.6 is the stronger model overall, scoring 41.4 to 28.2 on the Noometry Index. Ministral 8B costs 6.7× less per token, which makes it the better buy when GLM-4.6's lead doesn't matter for your workload.

Which is cheaper, GLM-4.6 or Ministral 8B?

Ministral 8B is cheaper. It lists at $0.15 per million input tokens and $0.15 per million output tokens; GLM-4.6 lists at $0.60 and $2.20.

Is GLM-4.6 or Ministral 8B better for coding?

GLM-4.6 scores higher on coding benchmarks: 40.1 versus 35.0 in the Noometry coding category.

Which has the bigger context window?

Ministral 8B does, with 262K tokens against 205K.

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

14 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Ministral 8B has 17.

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