Noometry

Model comparison

GLM-4.5V vs Mistral 7B

GLM-4.5V is the stronger model overall, scoring 39.8 to 23.0 on the Noometry Index. Mistral 7B costs 3.6× less per token, which makes it the better buy when GLM-4.5V's lead doesn't matter for your workload.

Last verified . 13 shared benchmarks.

GLM-4.5V Z.ai (Zhipu)

39.8

Rank #158 Confirmed

Mistral 7B Mistral AI

23.0

Rank #351 Confirmed

Summary

  • They share 13 benchmarks with published results for both. GLM-4.5V scores higher in 8 categories and Mistral 7B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.5V leads 37.5 to 7.4.
  • Mistral 7B is cheaper at $0.25 / $0.25 per million input/output tokens, against $0.60 / $1.80 for GLM-4.5V.
  • GLM-4.5V accepts more context: 64K tokens versus 8K.

Side by side

GLM-4.5VMistral 7B
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index39.823.0
Released2025-08-112023-09-27
WeightsOpenOpen
Context window64K8K
Max output16K8K
Input $ / M tokens$0.60$0.25
Output $ / M tokens$1.80$0.25
Results tracked1537

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Category by category

Coding GLM-4.5V leads

GLM-4.5V: 39.5 (#155), Mistral 7B: 26.4 (#326)

BenchmarkGLM-4.5VMistral 7B
LMArena Coding13471082
BigCodeBench Instruct—19.5%
BigCodeBench Complete—27.3%
HumanEval+—36%
MBPP+—42.1%

Reasoning GLM-4.5V leads

GLM-4.5V: 27.4 (#119), Mistral 7B: 13.1 (#336)

BenchmarkGLM-4.5VMistral 7B
LMArena Hard Prompts13341067
Kagi LLM Benchmark59.8%—
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-4.5V leads

GLM-4.5V: 37.4 (#159), Mistral 7B: 8.1 (#325)

BenchmarkGLM-4.5VMistral 7B
LMArena Math13541085
OTIS Mock AIME 2024-2025—0.3%
MATH Level 5—3.7%
GSM8K—54.4%

Knowledge GLM-4.5V leads

GLM-4.5V: 37.5 (#156), Mistral 7B: 7.4 (#311)

BenchmarkGLM-4.5VMistral 7B
LMArena Expert13531036
GPQA Diamond—15.2%
ARC (AI2) Challenge—78.6%
BoolQ—87.4%
MMLU—62.5%
OpenBookQA—79.8%
TriviaQA—75.2%

Multimodal Not comparable

GLM-4.5V: 34.3 (#92), Mistral 7B: —

BenchmarkGLM-4.5VMistral 7B
LMArena Vision1154—

Multilingual GLM-4.5V leads

GLM-4.5V: 44.6 (#177), Mistral 7B: 25.8 (#283)

BenchmarkGLM-4.5VMistral 7B
LMArena Non-English13031012
LMArena Chinese13371009
LMArena Russian12981018
LMArena Spanish13361026
LMArena French—1037
LMArena German—987
LMArena Japanese—878

Instruction Following GLM-4.5V leads

GLM-4.5V: 69.2 (#175), Mistral 7B: 54.2 (#280)

BenchmarkGLM-4.5VMistral 7B
LMArena Instruction Following13111060

Long Context GLM-4.5V leads

GLM-4.5V: 39.6 (#171), Mistral 7B: 32.2 (#271)

BenchmarkGLM-4.5VMistral 7B
LMArena Longer Query13041060

Writing & Preference GLM-4.5V leads

GLM-4.5V: 52.5 (#170), Mistral 7B: 30.7 (#286)

BenchmarkGLM-4.5VMistral 7B
LMArena Text13331090
LMArena Creative Writing12951068
LMArena Multi-Turn13321062

Frequently asked questions

Is GLM-4.5V better than Mistral 7B?

GLM-4.5V is the stronger model overall, scoring 39.8 to 23.0 on the Noometry Index. Mistral 7B costs 3.6× less per token, which makes it the better buy when GLM-4.5V's lead doesn't matter for your workload.

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

Mistral 7B is cheaper. It lists at $0.25 per million input tokens and $0.25 per million output tokens; GLM-4.5V lists at $0.60 and $1.80.

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

GLM-4.5V scores higher on coding benchmarks: 39.5 versus 26.4 in the Noometry coding category.

Which has the bigger context window?

GLM-4.5V does, with 64K tokens against 8K.

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

13 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and Mistral 7B has 37.

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