Noometry

Model comparison

GLM-4.5 vs Mistral 7B

GLM-4.5 is the stronger model overall, scoring 42.0 to 23.0 on the Noometry Index. Mistral 7B costs 4.0× less per token, which makes it the better buy when GLM-4.5's lead doesn't matter for your workload.

Last verified . 16 shared benchmarks.

GLM-4.5 Z.ai (Zhipu)

42.0

Rank #122 Confirmed

Mistral 7B Mistral AI

23.0

Rank #351 Confirmed

Summary

  • They share 16 benchmarks with published results for both. GLM-4.5 scores higher in 8 categories and Mistral 7B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-4.5 leads 39.0 to 8.1.
  • Mistral 7B is cheaper at $0.25 / $0.25 per million input/output tokens, against $0.60 / $2.20 for GLM-4.5.
  • GLM-4.5 accepts more context: 131K tokens versus 8K.

Side by side

GLM-4.5Mistral 7B
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index42.023.0
Released2025-07-272023-09-27
WeightsOpenOpen
Context window131K8K
Max output98K8K
Input $ / M tokens$0.60$0.25
Output $ / M tokens$2.20$0.25
Results tracked2737

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Category by category

Coding GLM-4.5 leads

GLM-4.5: 41.4 (#125), Mistral 7B: 26.4 (#326)

BenchmarkGLM-4.5Mistral 7B
LMArena Coding14341082
SWE-bench Verified (bash only)54.2%—
WeirdML40.6%—
BigCodeBench Instruct—19.5%
BigCodeBench Complete—27.3%
ALE-Bench344.82—
AlgoTune1.52—
HumanEval+—36%
MBPP+—42.1%

Reasoning GLM-4.5 leads

GLM-4.5: 28.6 (#100), Mistral 7B: 13.1 (#336)

BenchmarkGLM-4.5Mistral 7B
LMArena Hard Prompts14291067
Kagi LLM Benchmark57.9%—
Chess Puzzles—0%
DTBench—42.5%
Adversarial NLI—47.1%
BIG-Bench Hard—56.1%
Epoch Capabilities Index—112.21
HellaSwag—81%
PIQA—83%
WinoGrande—75.3%

Math GLM-4.5 leads

GLM-4.5: 39.0 (#116), Mistral 7B: 8.1 (#325)

BenchmarkGLM-4.5Mistral 7B
LMArena Math14271085
OTIS Mock AIME 2024-2025—0.3%
MATH Level 5—3.7%
GSM8K—54.4%

Knowledge GLM-4.5 leads

GLM-4.5: 35.9 (#179), Mistral 7B: 7.4 (#311)

BenchmarkGLM-4.5Mistral 7B
LMArena Expert14331036
GPQA Diamond—15.2%
Humanity's Last Exam8.3%—
Confabulations11.3%—
ARC (AI2) Challenge—78.6%
BoolQ—87.4%
MMLU—62.5%
OpenBookQA—79.8%
TriviaQA—75.2%

Multilingual GLM-4.5 leads

GLM-4.5: 52.8 (#77), Mistral 7B: 25.8 (#283)

BenchmarkGLM-4.5Mistral 7B
LMArena Non-English14171012
LMArena Chinese14651009
LMArena French14181037
LMArena German1407987
LMArena Japanese1415878
LMArena Russian14141018
LMArena Spanish14541026
LMArena Korean1380—

Instruction Following GLM-4.5 leads

GLM-4.5: 74.1 (#104), Mistral 7B: 54.2 (#280)

BenchmarkGLM-4.5Mistral 7B
LMArena Instruction Following14041060

Long Context GLM-4.5 leads

GLM-4.5: 38.2 (#201), Mistral 7B: 32.2 (#271)

BenchmarkGLM-4.5Mistral 7B
LMArena Longer Query14121060
Fiction.LiveBench58.3%—

Writing & Preference GLM-4.5 leads

GLM-4.5: 57.5 (#127), Mistral 7B: 30.7 (#286)

BenchmarkGLM-4.5Mistral 7B
LMArena Text14301090
LMArena Creative Writing13951068
LMArena Multi-Turn14151062
Short-Story Creative Writing73.4%—
EQ-Bench Creative Writing1343—

Frequently asked questions

Is GLM-4.5 better than Mistral 7B?

GLM-4.5 is the stronger model overall, scoring 42.0 to 23.0 on the Noometry Index. Mistral 7B costs 4.0× less per token, which makes it the better buy when GLM-4.5's lead doesn't matter for your workload.

Which is cheaper, GLM-4.5 or Mistral 7B?

Mistral 7B is cheaper. It lists at $0.25 per million input tokens and $0.25 per million output tokens; GLM-4.5 lists at $0.60 and $2.20.

Is GLM-4.5 or Mistral 7B better for coding?

GLM-4.5 scores higher on coding benchmarks: 41.4 versus 26.4 in the Noometry coding category.

Which has the bigger context window?

GLM-4.5 does, with 131K tokens against 8K.

How many benchmarks do GLM-4.5 and Mistral 7B share?

16 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Mistral 7B has 37.

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