Noometry

Model comparison

GLM-4.7 vs Mixtral 8x7B

GLM-4.7 is the stronger model overall, scoring 42.0 to 27.1 on the Noometry Index.

Last verified . 19 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

42.0

Rank #124 Confirmed

Mixtral 8x7B Mistral AI

27.1

Rank #334 Confirmed

Summary

  • They share 19 benchmarks with published results for both. GLM-4.7 scores higher in 8 categories and Mixtral 8x7B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.7 leads 47.0 to 11.0.
  • The biggest single-benchmark swing is GPQA Diamond: 83.3% for GLM-4.7 and 30.6% for Mixtral 8x7B.
  • Mixtral 8x7B is cheaper at $0.70 / $0.70 per million input/output tokens, against $0.60 / $2.20 for GLM-4.7.
  • GLM-4.7 accepts more context: 205K tokens versus 32K.

Side by side

GLM-4.7Mixtral 8x7B
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index42.027.1
Released2025-12-222023-12-11
WeightsOpenOpen
Context window205K32K
Max output131K32K
Input $ / M tokens$0.60$0.70
Output $ / M tokens$2.20$0.70
Results tracked3638

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Category by category

Coding GLM-4.7 leads

GLM-4.7: 44.0 (#79), Mixtral 8x7B: 32.8 (#269)

BenchmarkGLM-4.7Mixtral 8x7B
LMArena Coding14541126
LMArena WebDev1435—
SciCode45.1%—
ALE-Bench399.48—
HumanEval+—39.6%
MBPP+—49.7%

Agentic & Tool Use Not comparable

GLM-4.7: 26.5 (#103), Mixtral 8x7B: —

BenchmarkGLM-4.7Mixtral 8x7B
Terminal-Bench33.4%—
Vending-Bench 22,377—

Reasoning GLM-4.7 leads

GLM-4.7: 24.3 (#164), Mixtral 8x7B: 18.2 (#285)

BenchmarkGLM-4.7Mixtral 8x7B
LMArena Hard Prompts14431115
Epoch Capabilities Index143.51118.47
SimpleBench47.7%—
CritPt1.7%—
Chess Puzzles6%—
DTBench—49.6%
Adversarial NLI—55.2%
ForecastBench—56.3
HellaSwag—86.7%
PIQA—83.6%
WinoGrande—77.2%

Math GLM-4.7 leads

GLM-4.7: 38.6 (#135), Mixtral 8x7B: 18.8 (#289)

BenchmarkGLM-4.7Mixtral 8x7B
LMArena Math14231147
OTIS Mock AIME 2024-202583.3%—
ProofBench6%—
Omni-MATH—10.5%
MATH Level 5—10%
FrontierMath (Feb 2025 set)2.4%—
FrontierMath Tier 4 (v1)0%—
GSM8K—74.4%

Knowledge GLM-4.7 leads

GLM-4.7: 47.0 (#80), Mixtral 8x7B: 11.0 (#301)

BenchmarkGLM-4.7Mixtral 8x7B
GPQA Diamond83.3%30.6%
LMArena Expert14241088
SimpleQA Verified32.2%—
MMLU-Pro—33.5%
Vectara Hallucination Rate11.7%—
GPQA (HELM)—29.6%
ARC (AI2) Challenge—87.3%
MMLU—70.6%
OpenBookQA—85.8%
TriviaQA—82.2%

Multilingual GLM-4.7 leads

GLM-4.7: 52.8 (#79), Mixtral 8x7B: 29.6 (#266)

BenchmarkGLM-4.7Mixtral 8x7B
LMArena Non-English14171077
LMArena Chinese14951055
LMArena French14321166
LMArena German14241114
LMArena Japanese1439931
LMArena Korean1399968
LMArena Russian14231090
LMArena Spanish14341111

Instruction Following GLM-4.7 leads

GLM-4.7: 74.4 (#95), Mixtral 8x7B: 51.0 (#297)

BenchmarkGLM-4.7Mixtral 8x7B
LMArena Instruction Following14111109
IFEval—57.5%

Long Context GLM-4.7 leads

GLM-4.7: 42.8 (#116), Mixtral 8x7B: 33.4 (#260)

BenchmarkGLM-4.7Mixtral 8x7B
LMArena Longer Query14321103
CL-bench15.9%—
CL-bench Life10.9%—

Writing & Preference GLM-4.7 leads

GLM-4.7: 60.9 (#93), Mixtral 8x7B: 34.2 (#270)

BenchmarkGLM-4.7Mixtral 8x7B
LMArena Text14351132
LMArena Creative Writing14011109
LMArena Multi-Turn14461115
EQ-Bench Creative Writing1413—
WildBench—67.3%

Frequently asked questions

Is GLM-4.7 better than Mixtral 8x7B?

GLM-4.7 is the stronger model overall, scoring 42.0 to 27.1 on the Noometry Index.

Which is cheaper, GLM-4.7 or Mixtral 8x7B?

Mixtral 8x7B is cheaper. It lists at $0.70 per million input tokens and $0.70 per million output tokens; GLM-4.7 lists at $0.60 and $2.20.

Is GLM-4.7 or Mixtral 8x7B better for coding?

GLM-4.7 scores higher on coding benchmarks: 44.0 versus 32.8 in the Noometry coding category.

Which has the bigger context window?

GLM-4.7 does, with 205K tokens against 32K.

How many benchmarks do GLM-4.7 and Mixtral 8x7B share?

19 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Mixtral 8x7B has 38.

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