Noometry

Model comparison

GLM-5.3 vs Magistral Medium

GLM-5.3 is the stronger model overall, scoring 54.8 to 35.2 on the Noometry Index.

Last verified . 19 shared benchmarks.

GLM-5.3 Z.ai (Zhipu)

54.8

Rank #26 Confirmed

Magistral Medium Mistral AI

35.2

Rank #227 Confirmed

Summary

  • They share 19 benchmarks with published results for both. GLM-5.3 scores higher in 8 categories and Magistral Medium in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-5.3 leads 46.1 to 8.6.
  • The biggest single-benchmark swing is SciCode: 59% for GLM-5.3 and 39.2% for Magistral Medium.
  • GLM-5.3 is cheaper at $1.40 / $4.40 per million input/output tokens, against $2 / $5 for Magistral Medium.
  • GLM-5.3 accepts more context: 1M tokens versus 262K.

Side by side

GLM-5.3Magistral Medium
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index54.835.2
Released2026-08-142025-03-17
WeightsOpenOpen
Context window1M262K
Max output131K16K
Input $ / M tokens$1.40$2
Output $ / M tokens$4.40$5
Results tracked4222

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Category by category

Coding GLM-5.3 leads

GLM-5.3: 59.5 (#14), Magistral Medium: 39.1 (#161)

BenchmarkGLM-5.3Magistral Medium
SciCode59%39.2%
LMArena Coding14961319
DeepSWE69%—
FrontierCode40.1%—
CursorBench42.6%—
LMArena WebDev1622—
FrontierSWE30.2%—
WeirdML75.4%—
ALE-Bench1,317—

Agentic & Tool Use Not comparable

GLM-5.3: 36.4 (#38), Magistral Medium: —

BenchmarkGLM-5.3Magistral Medium
APEX-Agents56.6%—
Vending-Bench 28,164—

Reasoning GLM-5.3 leads

GLM-5.3: 46.1 (#46), Magistral Medium: 8.6 (#348)

BenchmarkGLM-5.3Magistral Medium
CritPt19.1%0.3%
LMArena Hard Prompts14891267
ARC-AGI-2—0%
Kagi LLM Benchmark—16.2%
NYT Connections (extended)74.2%—
ARC-AGI-1—6.1%
Chess Puzzles21%—
Mystery Game Puzzles33%—
DTBench87.7%—
LMCA55.5%—
Bench to the Future 30.15—
Epoch Capabilities Index155.61—

Math GLM-5.3 leads

GLM-5.3: 62.3 (#33), Magistral Medium: 35.1 (#189)

BenchmarkGLM-5.3Magistral Medium
LMArena Math14891250
FrontierMath (Tiers 1-3)68.8%—
FrontierMath Tier 429.3%—
OTIS Mock AIME 2024-202591.1%—
ProofBench49%—

Knowledge GLM-5.3 leads

GLM-5.3: 58.3 (#37), Magistral Medium: 33.5 (#202)

BenchmarkGLM-5.3Magistral Medium
LMArena Expert15161223
GPQA Diamond90.9%—
SimpleQA Verified41%—

Multilingual GLM-5.3 leads

GLM-5.3: 55.7 (#28), Magistral Medium: 39.6 (#224)

BenchmarkGLM-5.3Magistral Medium
LMArena Non-English14571232
LMArena Chinese15281227
LMArena French14991267
LMArena German14991248
LMArena Japanese14531175
LMArena Korean14721125
LMArena Russian14631224
LMArena Spanish14601271

Instruction Following GLM-5.3 leads

GLM-5.3: 77.5 (#23), Magistral Medium: 66.0 (#211)

BenchmarkGLM-5.3Magistral Medium
LMArena Instruction Following14771254

Long Context GLM-5.3 leads

GLM-5.3: 45.4 (#41), Magistral Medium: 39.3 (#183)

BenchmarkGLM-5.3Magistral Medium
LMArena Longer Query14821295

Writing & Preference GLM-5.3 leads

GLM-5.3: 75.7 (#6), Magistral Medium: 46.3 (#219)

BenchmarkGLM-5.3Magistral Medium
LMArena Text14711255
LMArena Creative Writing14571245
LMArena Multi-Turn14721275
EQ-Bench Creative Writing2075—

Frequently asked questions

Is GLM-5.3 better than Magistral Medium?

GLM-5.3 is the stronger model overall, scoring 54.8 to 35.2 on the Noometry Index.

Which is cheaper, GLM-5.3 or Magistral Medium?

GLM-5.3 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; Magistral Medium lists at $2 and $5.

Is GLM-5.3 or Magistral Medium better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.5 versus 39.1 in the Noometry coding category.

Which has the bigger context window?

GLM-5.3 does, with 1M tokens against 262K.

How many benchmarks do GLM-5.3 and Magistral Medium share?

19 benchmarks have published results for both models. GLM-5.3 has 42 scored results on Noometry and Magistral Medium has 22.

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