Model comparison

GLM-5.3 vs Mercury

GLM-5.3 is the stronger model overall, scoring 54.8 to 37.6 on the Noometry Index.

Last verified . 8 shared benchmarks.

GLM-5.3 Z.ai (Zhipu)

54.8

Rank #26 Confirmed

Mercury Inception

37.6

Rank #199 Confirmed

Summary

  • They share 8 benchmarks with published results for both. GLM-5.3 scores higher in 6 categories and Mercury in 0 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-5.3 leads 75.7 to 46.2.
  • GLM-5.3 has downloadable open weights; the other is API-only.

Side by side

GLM-5.3 and Mercury specifications
GLM-5.3Mercury
ProviderZ.ai (Zhipu)Inception
Noometry Index54.837.6
Released2026-08-14—
WeightsOpenProprietary
Context window1M—
Max output131K—
Input $ / M tokens$1.40—
Output $ / M tokens$4.40—
Results tracked429

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding GLM-5.3 leads

GLM-5.3: 59.5 (#14), Mercury: 38.7 (#170)

Coding benchmarks
BenchmarkGLM-5.3Mercury
LMArena Coding14961322
DeepSWE69%—
FrontierCode40.1%—
CursorBench42.6%—
LMArena WebDev1622—
FrontierSWE30.2%—
SciCode59%—
WeirdML75.4%—
ALE-Bench1,317—

Agentic & Tool Use Not comparable

GLM-5.3: 36.4 (#38), Mercury: —

Agentic & Tool Use benchmarks
BenchmarkGLM-5.3Mercury
APEX-Agents56.6%—
Vending-Bench 28,164—

Reasoning GLM-5.3 leads

GLM-5.3: 46.1 (#46), Mercury: 17.5 (#293)

Reasoning benchmarks
BenchmarkGLM-5.3Mercury
LMArena Hard Prompts14891285
Kagi LLM Benchmark—21.6%
NYT Connections (extended)74.2%—
CritPt19.1%—
Chess Puzzles21%—
Mystery Game Puzzles33%—
DTBench87.7%—
LMCA55.5%—
Bench to the Future 30.15—
Epoch Capabilities Index155.61—

Math Not comparable

GLM-5.3: 62.3 (#33), Mercury: —

Math benchmarks
BenchmarkGLM-5.3Mercury
FrontierMath (Tiers 1-3)68.8%—
FrontierMath Tier 429.3%—
OTIS Mock AIME 2024-202591.1%—
ProofBench49%—
LMArena Math1489—

Knowledge Not comparable

GLM-5.3: 58.3 (#37), Mercury: —

Knowledge benchmarks
BenchmarkGLM-5.3Mercury
GPQA Diamond90.9%—
SimpleQA Verified41%—
LMArena Expert1516—

Multilingual GLM-5.3 leads

GLM-5.3: 55.7 (#28), Mercury: 41.6 (#206)

Multilingual benchmarks
BenchmarkGLM-5.3Mercury
LMArena Non-English14571260
LMArena Chinese1528—
LMArena French1499—
LMArena German1499—
LMArena Japanese1453—
LMArena Korean1472—
LMArena Russian1463—
LMArena Spanish1460—

Instruction Following GLM-5.3 leads

GLM-5.3: 77.5 (#23), Mercury: 65.2 (#224)

Instruction Following benchmarks
BenchmarkGLM-5.3Mercury
LMArena Instruction Following14771239

Long Context GLM-5.3 leads

GLM-5.3: 45.4 (#41), Mercury: 38.4 (#198)

Long Context benchmarks
BenchmarkGLM-5.3Mercury
LMArena Longer Query14821266

Writing & Preference GLM-5.3 leads

GLM-5.3: 75.7 (#6), Mercury: 46.2 (#221)

Writing & Preference benchmarks
BenchmarkGLM-5.3Mercury
LMArena Text14711282
LMArena Creative Writing14571191
LMArena Multi-Turn14721282
EQ-Bench Creative Writing2075—

Frequently asked questions

Is GLM-5.3 better than Mercury?

GLM-5.3 is the stronger model overall, scoring 54.8 to 37.6 on the Noometry Index.

Is GLM-5.3 or Mercury better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.5 versus 38.7 in the Noometry coding category.

How many benchmarks do GLM-5.3 and Mercury share?

8 benchmarks have published results for both models. GLM-5.3 has 42 scored results on Noometry and Mercury has 9.

Related comparisons

Go deeper