Noometry

Model comparison

GLM-5.3-Flash vs Pixtral Large

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 32.2 on the Noometry Index.

Last verified . 1 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

Pixtral Large Mistral AI

32.2

Rank #259 Reported

Summary

  • They share 1 benchmark with published results for both. GLM-5.3-Flash scores higher in 3 categories and Pixtral Large in 0 categories; 3 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-5.3-Flash leads 65.3 to 32.9.
  • GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $2 / $6 for Pixtral Large.
  • GLM-5.3-Flash accepts more context: 1M tokens versus 128K.

Side by side

GLM-5.3-FlashPixtral Large
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index51.832.2
Released2026-08-202024-11-01
WeightsOpenOpen
Context window1M128K
Max output131K128K
Input $ / M tokens$0.15$2
Output $ / M tokens$0.50$6
Results tracked403

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Category by category

Coding Not comparable

GLM-5.3-Flash: 53.1 (#31), Pixtral Large: —

BenchmarkGLM-5.3-FlashPixtral Large
DeepSWE63.4%—
FrontierCode31.8%—
CursorBench36.8%—
LMArena WebDev1609—
FrontierSWE18.1%—
SciCode51.6%—
LMArena Coding1508—
ALE-Bench303.55—

Agentic & Tool Use Not comparable

GLM-5.3-Flash: 34.2 (#47), Pixtral Large: —

BenchmarkGLM-5.3-FlashPixtral Large
APEX-Agents52.8%—
GDP.pdf14%—

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 48.0 (#42), Pixtral Large: 21.7 (#218)

BenchmarkGLM-5.3-FlashPixtral Large
ARC-AGI-265.8%—
ARC-AGI-191%—
CritPt15.4%—
Chess Puzzles14%—
EnigmaEval—0.8%
LMArena Hard Prompts1491—
Mystery Game Puzzles8%—
Surface Evolver Bench52.5%—
Bench to the Future 30.15—
Epoch Capabilities Index151.88—

Math Not comparable

GLM-5.3-Flash: 53.3 (#47), Pixtral Large: —

BenchmarkGLM-5.3-FlashPixtral Large
FrontierMath (Tiers 1-3)55.8%—
FrontierMath Tier 417.1%—
OTIS Mock AIME 2024-202593.9%—
ProofBench21%—
LMArena Math1500—

Knowledge Not comparable

GLM-5.3-Flash: 58.4 (#36), Pixtral Large: —

BenchmarkGLM-5.3-FlashPixtral Large
GPQA Diamond90.2%—
LMArena Expert1513—

Multimodal GLM-5.3-Flash leads

GLM-5.3-Flash: 42.8 (#27), Pixtral Large: 30.6 (#111)

BenchmarkGLM-5.3-FlashPixtral Large
LMArena Vision12961089

Multilingual Not comparable

GLM-5.3-Flash: 56.0 (#25), Pixtral Large: —

BenchmarkGLM-5.3-FlashPixtral Large
LMArena Non-English1462—
LMArena Chinese1527—
LMArena French1496—
LMArena German1470—
LMArena Japanese1429—
LMArena Korean1446—
LMArena Russian1469—
LMArena Spanish1471—

Instruction Following Not comparable

GLM-5.3-Flash: 77.5 (#20), Pixtral Large: —

BenchmarkGLM-5.3-FlashPixtral Large
LMArena Instruction Following1478—

Long Context Not comparable

GLM-5.3-Flash: 45.4 (#39), Pixtral Large: —

BenchmarkGLM-5.3-FlashPixtral Large
LMArena Longer Query1482—

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.3 (#50), Pixtral Large: 32.9 (#278)

BenchmarkGLM-5.3-FlashPixtral Large
LMArena Text1471—
LMArena Creative Writing1442—
EQ-Bench Creative Writing—988
LMArena Multi-Turn1467—

Frequently asked questions

Is GLM-5.3-Flash better than Pixtral Large?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 32.2 on the Noometry Index.

Which is cheaper, GLM-5.3-Flash or Pixtral Large?

GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; Pixtral Large lists at $2 and $6.

Which has the bigger context window?

GLM-5.3-Flash does, with 1M tokens against 128K.

How many benchmarks do GLM-5.3-Flash and Pixtral Large share?

1 benchmark has published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and Pixtral Large has 3.

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