Model comparison

GLM-4.6 vs Mercury

GLM-4.6 is the stronger model overall, scoring 41.4 to 37.6 on the Noometry Index.

Last verified . 9 shared benchmarks.

GLM-4.6 Z.ai (Zhipu)

41.4

Rank #135 Confirmed

Mercury Inception

37.6

Rank #199 Confirmed

Summary

  • They share 9 benchmarks with published results for both. GLM-4.6 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-4.6 leads 61.1 to 46.2.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 47.4% for GLM-4.6 and 21.6% for Mercury.
  • GLM-4.6 has downloadable open weights; the other is API-only.

Side by side

GLM-4.6 and Mercury specifications
GLM-4.6Mercury
ProviderZ.ai (Zhipu)Inception
Noometry Index41.437.6
Released2025-09-30—
WeightsOpenProprietary
Context window205K—
Max output131K—
Input $ / M tokens$0.60—
Output $ / M tokens$2.20—
Results tracked299

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Category by category

Coding GLM-4.6 leads

GLM-4.6: 40.1 (#148), Mercury: 38.7 (#170)

Coding benchmarks
BenchmarkGLM-4.6Mercury
LMArena Coding14491322
SWE-bench Verified (bash only)55.4%—
LMArena WebDev1340—
SciCode38.4%—
ALE-Bench340.82—

Agentic & Tool Use Not comparable

GLM-4.6: 32.3 (#66), Mercury: —

Agentic & Tool Use benchmarks
BenchmarkGLM-4.6Mercury
Terminal-Bench24.5%—
Berkeley Function Calling Leaderboard72.4%—

Reasoning GLM-4.6 leads

GLM-4.6: 23.7 (#172), Mercury: 17.5 (#293)

Reasoning benchmarks
BenchmarkGLM-4.6Mercury
Kagi LLM Benchmark47.4%21.6%
LMArena Hard Prompts14401285
CritPt1.1%—

Math Not comparable

GLM-4.6: 39.1 (#111), Mercury: —

Math benchmarks
BenchmarkGLM-4.6Mercury
LMArena Math1432—
FrontierMath (Feb 2025 set)3.8%—
FrontierMath Tier 4 (v1)2.1%—

Knowledge Not comparable

GLM-4.6: 40.2 (#124), Mercury: —

Knowledge benchmarks
BenchmarkGLM-4.6Mercury
Vectara Hallucination Rate9.5%—
LMArena Expert1431—

Multilingual GLM-4.6 leads

GLM-4.6: 53.5 (#66), Mercury: 41.6 (#206)

Multilingual benchmarks
BenchmarkGLM-4.6Mercury
LMArena Non-English14261260
LMArena Chinese1499—
LMArena French1459—
LMArena German1447—
LMArena Japanese1393—
LMArena Korean1400—
LMArena Russian1419—
LMArena Spanish1436—

Instruction Following GLM-4.6 leads

GLM-4.6: 74.3 (#98), Mercury: 65.2 (#224)

Instruction Following benchmarks
BenchmarkGLM-4.6Mercury
LMArena Instruction Following14101239

Long Context GLM-4.6 leads

GLM-4.6: 43.4 (#94), Mercury: 38.4 (#198)

Long Context benchmarks
BenchmarkGLM-4.6Mercury
LMArena Longer Query14221266

Writing & Preference GLM-4.6 leads

GLM-4.6: 61.1 (#90), Mercury: 46.2 (#221)

Writing & Preference benchmarks
BenchmarkGLM-4.6Mercury
LMArena Text14401282
LMArena Creative Writing14111191
LMArena Multi-Turn14271282
EQ-Bench Creative Writing1411—

Frequently asked questions

Is GLM-4.6 better than Mercury?

GLM-4.6 is the stronger model overall, scoring 41.4 to 37.6 on the Noometry Index.

Is GLM-4.6 or Mercury better for coding?

GLM-4.6 scores higher on coding benchmarks: 40.1 versus 38.7 in the Noometry coding category.

How many benchmarks do GLM-4.6 and Mercury share?

9 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Mercury has 9.

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