Noometry

Model comparison

GLM-4.5-Air vs Mixtral 8x7B

GLM-4.5-Air is the stronger model overall, scoring 38.9 to 27.1 on the Noometry Index.

Last verified . 23 shared benchmarks.

GLM-4.5-Air Z.ai (Zhipu)

38.9

Rank #177 Confirmed

Mixtral 8x7B Mistral AI

27.1

Rank #334 Confirmed

Summary

  • They share 23 benchmarks with published results for both. GLM-4.5-Air scores higher in 8 categories and Mixtral 8x7B in 0 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.5-Air leads 35.0 to 11.0.
  • The biggest single-benchmark swing is MMLU-Pro: 76.2% for GLM-4.5-Air and 33.5% for Mixtral 8x7B.
  • GLM-4.5-Air is cheaper at $0.20 / $1.10 per million input/output tokens, against $0.70 / $0.70 for Mixtral 8x7B.
  • GLM-4.5-Air accepts more context: 131K tokens versus 32K.

Side by side

GLM-4.5-AirMixtral 8x7B
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index38.927.1
Released2025-07-202023-12-11
WeightsOpenOpen
Context window131K32K
Max output98K32K
Input $ / M tokens$0.20$0.70
Output $ / M tokens$1.10$0.70
Results tracked2738

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Category by category

Coding Too close to call

GLM-4.5-Air: 33.3 (#259), Mixtral 8x7B: 32.8 (#269)

BenchmarkGLM-4.5-AirMixtral 8x7B
LMArena Coding13971126
GSO2.9%—
HumanEval+—39.6%
MBPP+—49.7%

Reasoning GLM-4.5-Air leads

GLM-4.5-Air: 24.1 (#166), Mixtral 8x7B: 18.2 (#285)

BenchmarkGLM-4.5-AirMixtral 8x7B
LMArena Hard Prompts13791115
ForecastBench59.256.3
Kagi LLM Benchmark43%—
DTBench—49.6%
Adversarial NLI—55.2%
Epoch Capabilities Index—118.47
HellaSwag—86.7%
PIQA—83.6%
WinoGrande—77.2%

Math GLM-4.5-Air leads

GLM-4.5-Air: 36.2 (#170), Mixtral 8x7B: 18.8 (#289)

BenchmarkGLM-4.5-AirMixtral 8x7B
Omni-MATH39.1%10.5%
LMArena Math13961147
MATH Level 5—10%
GSM8K—74.4%

Knowledge GLM-4.5-Air leads

GLM-4.5-Air: 35.0 (#191), Mixtral 8x7B: 11.0 (#301)

BenchmarkGLM-4.5-AirMixtral 8x7B
MMLU-Pro76.2%33.5%
GPQA (HELM)59.4%29.6%
LMArena Expert13701088
GPQA Diamond—30.6%
Humanity's Last Exam8.1%—
Vectara Hallucination Rate9.3%—
ARC (AI2) Challenge—87.3%
MMLU—70.6%
OpenBookQA—85.8%
TriviaQA—82.2%

Multilingual GLM-4.5-Air leads

GLM-4.5-Air: 49.1 (#135), Mixtral 8x7B: 29.6 (#266)

BenchmarkGLM-4.5-AirMixtral 8x7B
LMArena Non-English13661077
LMArena Chinese14261055
LMArena French13991166
LMArena German13771114
LMArena Japanese1348931
LMArena Korean1308968
LMArena Russian13731090
LMArena Spanish13861111

Instruction Following GLM-4.5-Air leads

GLM-4.5-Air: 69.6 (#171), Mixtral 8x7B: 51.0 (#297)

BenchmarkGLM-4.5-AirMixtral 8x7B
IFEval81.2%57.5%
LMArena Instruction Following13541109

Long Context GLM-4.5-Air leads

GLM-4.5-Air: 41.6 (#135), Mixtral 8x7B: 33.4 (#260)

BenchmarkGLM-4.5-AirMixtral 8x7B
LMArena Longer Query13661103

Writing & Preference GLM-4.5-Air leads

GLM-4.5-Air: 55.9 (#139), Mixtral 8x7B: 34.2 (#270)

BenchmarkGLM-4.5-AirMixtral 8x7B
LMArena Text13841132
LMArena Creative Writing13431109
WildBench78.9%67.3%
LMArena Multi-Turn13711115

Frequently asked questions

Is GLM-4.5-Air better than Mixtral 8x7B?

GLM-4.5-Air is the stronger model overall, scoring 38.9 to 27.1 on the Noometry Index.

Which is cheaper, GLM-4.5-Air or Mixtral 8x7B?

GLM-4.5-Air is cheaper. It lists at $0.20 per million input tokens and $1.10 per million output tokens; Mixtral 8x7B lists at $0.70 and $0.70.

Is GLM-4.5-Air or Mixtral 8x7B better for coding?

They score almost the same on coding (33.3 vs 32.8); test both on your own repository before choosing.

Which has the bigger context window?

GLM-4.5-Air does, with 131K tokens against 32K.

How many benchmarks do GLM-4.5-Air and Mixtral 8x7B share?

23 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and Mixtral 8x7B has 38.

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