Model comparison

GLM-5.3 vs Llama 3.1-405B

GLM-5.3 is the stronger model overall, scoring 54.8 to 30.7 on the Noometry Index.

Last verified . 23 shared benchmarks.

GLM-5.3 Z.ai (Zhipu)

54.8

Rank #26 Confirmed

Llama 3.1-405B Meta

30.7

Rank #288 Confirmed

Summary

  • They share 23 benchmarks with published results for both. GLM-5.3 scores higher in 9 categories and Llama 3.1-405B in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-5.3 leads 62.3 to 18.4.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 91.1% for GLM-5.3 and 9.7% for Llama 3.1-405B.

Side by side

GLM-5.3 and Llama 3.1-405B specifications
GLM-5.3Llama 3.1-405B
ProviderZ.ai (Zhipu)Meta
Noometry Index54.830.7
Released2026-08-142024-07-23
WeightsOpenOpen
Context window1M—
Max output131K—
Input $ / M tokens$1.40—
Output $ / M tokens$4.40—
Results tracked4242

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Category by category

Coding GLM-5.3 leads

GLM-5.3: 59.5 (#14), Llama 3.1-405B: 33.1 (#262)

Coding benchmarks
BenchmarkGLM-5.3Llama 3.1-405B
WeirdML75.4%21.4%
LMArena Coding14961291
DeepSWE69%—
FrontierCode40.1%—
CursorBench42.6%—
LMArena WebDev1622—
FrontierSWE30.2%—
SciCode59%—
ALE-Bench1,317—

Agentic & Tool Use GLM-5.3 leads

GLM-5.3: 36.4 (#38), Llama 3.1-405B: 21.0 (#140)

Agentic & Tool Use benchmarks
BenchmarkGLM-5.3Llama 3.1-405B
APEX-Agents56.6%—
TheAgentCompany—7.4%
Cybench—7.5%
Vending-Bench 28,164—

Reasoning GLM-5.3 leads

GLM-5.3: 46.1 (#46), Llama 3.1-405B: 16.8 (#300)

Reasoning benchmarks
BenchmarkGLM-5.3Llama 3.1-405B
LMArena Hard Prompts14891269
DTBench87.7%61.4%
Epoch Capabilities Index155.61128.75
SimpleBench—23%
Kagi LLM Benchmark—45%
NYT Connections (extended)74.2%—
CritPt19.1%—
Chess Puzzles21%—
Mystery Game Puzzles33%—
LMCA55.5%—
Bench to the Future 30.15—
BIG-Bench Hard—82.9%
ForecastBench—59.9
HellaSwag—89.2%
PIQA—85.9%
WinoGrande—89.2%

Math GLM-5.3 leads

GLM-5.3: 62.3 (#33), Llama 3.1-405B: 18.4 (#290)

Math benchmarks
BenchmarkGLM-5.3Llama 3.1-405B
OTIS Mock AIME 2024-202591.1%9.7%
LMArena Math14891281
FrontierMath (Tiers 1-3)68.8%—
FrontierMath Tier 429.3%—
ProofBench49%—
Omni-MATH—24.9%
MATH Level 5—49.8%

Knowledge GLM-5.3 leads

GLM-5.3: 58.3 (#37), Llama 3.1-405B: 30.4 (#227)

Knowledge benchmarks
BenchmarkGLM-5.3Llama 3.1-405B
GPQA Diamond90.9%50.9%
LMArena Expert15161243
SimpleQA Verified41%—
MMLU-Pro—72.3%
Confabulations—17.6%
GPQA (HELM)—52.2%
ARC (AI2) Challenge—95.3%
MMLU—84.5%
TriviaQA—82.7%

Multilingual GLM-5.3 leads

GLM-5.3: 55.7 (#28), Llama 3.1-405B: 40.7 (#214)

Multilingual benchmarks
BenchmarkGLM-5.3Llama 3.1-405B
LMArena Non-English14571248
LMArena Chinese15281242
LMArena French14991279
LMArena German14991252
LMArena Japanese14531208
LMArena Korean14721184
LMArena Russian14631265
LMArena Spanish14601260

Instruction Following GLM-5.3 leads

GLM-5.3: 77.5 (#23), Llama 3.1-405B: 65.9 (#214)

Instruction Following benchmarks
BenchmarkGLM-5.3Llama 3.1-405B
LMArena Instruction Following14771259
IFEval—81.1%

Long Context GLM-5.3 leads

GLM-5.3: 45.4 (#41), Llama 3.1-405B: 38.4 (#197)

Long Context benchmarks
BenchmarkGLM-5.3Llama 3.1-405B
LMArena Longer Query14821266

Writing & Preference GLM-5.3 leads

GLM-5.3: 75.7 (#6), Llama 3.1-405B: 38.9 (#251)

Writing & Preference benchmarks
BenchmarkGLM-5.3Llama 3.1-405B
LMArena Text14711284
LMArena Creative Writing14571262
EQ-Bench Creative Writing2075870
LMArena Multi-Turn14721297
WildBench—78.3%

Frequently asked questions

Is GLM-5.3 better than Llama 3.1-405B?

GLM-5.3 is the stronger model overall, scoring 54.8 to 30.7 on the Noometry Index.

Is GLM-5.3 or Llama 3.1-405B better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.5 versus 33.1 in the Noometry coding category.

How many benchmarks do GLM-5.3 and Llama 3.1-405B share?

23 benchmarks have published results for both models. GLM-5.3 has 42 scored results on Noometry and Llama 3.1-405B has 42.

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