Noometry

Model comparison

GLM-5.3-Flash vs Mixtral 8x7B

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 27.1 on the Noometry Index.

Last verified . 19 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

Mixtral 8x7B Mistral AI

27.1

Rank #334 Confirmed

Summary

  • They share 19 benchmarks with published results for both. GLM-5.3-Flash 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-5.3-Flash leads 58.4 to 11.0.
  • The biggest single-benchmark swing is GPQA Diamond: 90.2% for GLM-5.3-Flash and 30.6% for Mixtral 8x7B.
  • GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $0.70 / $0.70 for Mixtral 8x7B.
  • GLM-5.3-Flash accepts more context: 1M tokens versus 32K.

Side by side

GLM-5.3-FlashMixtral 8x7B
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index51.827.1
Released2026-08-202023-12-11
WeightsOpenOpen
Context window1M32K
Max output131K32K
Input $ / M tokens$0.15$0.70
Output $ / M tokens$0.50$0.70
Results tracked4038

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Category by category

Coding GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#31), Mixtral 8x7B: 32.8 (#269)

BenchmarkGLM-5.3-FlashMixtral 8x7B
LMArena Coding15081126
DeepSWE63.4%—
FrontierCode31.8%—
CursorBench36.8%—
LMArena WebDev1609—
FrontierSWE18.1%—
SciCode51.6%—
ALE-Bench303.55—
HumanEval+—39.6%
MBPP+—49.7%

Agentic & Tool Use Not comparable

GLM-5.3-Flash: 34.2 (#47), Mixtral 8x7B: —

BenchmarkGLM-5.3-FlashMixtral 8x7B
APEX-Agents52.8%—
GDP.pdf14%—

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 48.0 (#42), Mixtral 8x7B: 18.2 (#285)

BenchmarkGLM-5.3-FlashMixtral 8x7B
LMArena Hard Prompts14911115
Epoch Capabilities Index151.88118.47
ARC-AGI-265.8%—
ARC-AGI-191%—
CritPt15.4%—
Chess Puzzles14%—
Mystery Game Puzzles8%—
DTBench—49.6%
Surface Evolver Bench52.5%—
Adversarial NLI—55.2%
Bench to the Future 30.15—
ForecastBench—56.3
HellaSwag—86.7%
PIQA—83.6%
WinoGrande—77.2%

Math GLM-5.3-Flash leads

GLM-5.3-Flash: 53.3 (#47), Mixtral 8x7B: 18.8 (#289)

BenchmarkGLM-5.3-FlashMixtral 8x7B
LMArena Math15001147
FrontierMath (Tiers 1-3)55.8%—
FrontierMath Tier 417.1%—
OTIS Mock AIME 2024-202593.9%—
ProofBench21%—
Omni-MATH—10.5%
MATH Level 5—10%
GSM8K—74.4%

Knowledge GLM-5.3-Flash leads

GLM-5.3-Flash: 58.4 (#36), Mixtral 8x7B: 11.0 (#301)

BenchmarkGLM-5.3-FlashMixtral 8x7B
GPQA Diamond90.2%30.6%
LMArena Expert15131088
MMLU-Pro—33.5%
GPQA (HELM)—29.6%
ARC (AI2) Challenge—87.3%
MMLU—70.6%
OpenBookQA—85.8%
TriviaQA—82.2%

Multimodal Not comparable

GLM-5.3-Flash: 42.8 (#27), Mixtral 8x7B: —

BenchmarkGLM-5.3-FlashMixtral 8x7B
LMArena Vision1296—

Multilingual GLM-5.3-Flash leads

GLM-5.3-Flash: 56.0 (#25), Mixtral 8x7B: 29.6 (#266)

BenchmarkGLM-5.3-FlashMixtral 8x7B
LMArena Non-English14621077
LMArena Chinese15271055
LMArena French14961166
LMArena German14701114
LMArena Japanese1429931
LMArena Korean1446968
LMArena Russian14691090
LMArena Spanish14711111

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.5 (#20), Mixtral 8x7B: 51.0 (#297)

BenchmarkGLM-5.3-FlashMixtral 8x7B
LMArena Instruction Following14781109
IFEval—57.5%

Long Context GLM-5.3-Flash leads

GLM-5.3-Flash: 45.4 (#39), Mixtral 8x7B: 33.4 (#260)

BenchmarkGLM-5.3-FlashMixtral 8x7B
LMArena Longer Query14821103

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.3 (#50), Mixtral 8x7B: 34.2 (#270)

BenchmarkGLM-5.3-FlashMixtral 8x7B
LMArena Text14711132
LMArena Creative Writing14421109
LMArena Multi-Turn14671115
WildBench—67.3%

Frequently asked questions

Is GLM-5.3-Flash better than Mixtral 8x7B?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 27.1 on the Noometry Index.

Which is cheaper, GLM-5.3-Flash or Mixtral 8x7B?

GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; Mixtral 8x7B lists at $0.70 and $0.70.

Is GLM-5.3-Flash or Mixtral 8x7B better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 32.8 in the Noometry coding category.

Which has the bigger context window?

GLM-5.3-Flash does, with 1M tokens against 32K.

How many benchmarks do GLM-5.3-Flash and Mixtral 8x7B share?

19 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and Mixtral 8x7B has 38.

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