Model comparison

GLM-5.3 vs Llama 3-8B

GLM-5.3 is the stronger model overall, scoring 54.8 to 25.5 on the Noometry Index.

Last verified . 22 shared benchmarks.

GLM-5.3 Z.ai (Zhipu)

54.8

Rank #26 Confirmed

Llama 3-8B Meta

25.5

Rank #344 Confirmed

Summary

  • They share 22 benchmarks with published results for both. GLM-5.3 scores higher in 8 categories and Llama 3-8B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-5.3 leads 62.3 to 8.8.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 91.1% for GLM-5.3 and 1.9% for Llama 3-8B.

Side by side

GLM-5.3 and Llama 3-8B specifications
GLM-5.3Llama 3-8B
ProviderZ.ai (Zhipu)Meta
Noometry Index54.825.5
Released2026-08-142024-04-18
WeightsOpenOpen
Context window1M—
Max output131K—
Input $ / M tokens$1.40—
Output $ / M tokens$4.40—
Results tracked4234

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), Llama 3-8B: 31.0 (#289)

Coding benchmarks
BenchmarkGLM-5.3Llama 3-8B
LMArena Coding14961152
DeepSWE69%—
FrontierCode40.1%—
CursorBench42.6%—
LMArena WebDev1622—
FrontierSWE30.2%—
SciCode59%—
WeirdML75.4%—
BigCodeBench Instruct—31.9%
BigCodeBench Complete—36.9%
ALE-Bench1,317—
HumanEval+—56.7%
MBPP+—54.8%

Agentic & Tool Use Not comparable

GLM-5.3: 36.4 (#38), Llama 3-8B: —

Agentic & Tool Use benchmarks
BenchmarkGLM-5.3Llama 3-8B
APEX-Agents56.6%—
Vending-Bench 28,164—

Reasoning GLM-5.3 leads

GLM-5.3: 46.1 (#46), Llama 3-8B: 14.3 (#326)

Reasoning benchmarks
BenchmarkGLM-5.3Llama 3-8B
Chess Puzzles21%0%
LMArena Hard Prompts14891133
DTBench87.7%43.9%
Epoch Capabilities Index155.61116.45
NYT Connections (extended)74.2%—
CritPt19.1%—
Mystery Game Puzzles33%—
LMCA55.5%—
Adversarial NLI—57.3%
Bench to the Future 30.15—
ForecastBench—58.6
WinoGrande—75.7%

Math GLM-5.3 leads

GLM-5.3: 62.3 (#33), Llama 3-8B: 8.8 (#323)

Math benchmarks
BenchmarkGLM-5.3Llama 3-8B
OTIS Mock AIME 2024-202591.1%1.9%
LMArena Math14891151
FrontierMath (Tiers 1-3)68.8%—
FrontierMath Tier 429.3%—
ProofBench49%—
MATH Level 5—6.1%

Knowledge GLM-5.3 leads

GLM-5.3: 58.3 (#37), Llama 3-8B: 7.8 (#308)

Knowledge benchmarks
BenchmarkGLM-5.3Llama 3-8B
GPQA Diamond90.9%26.1%
LMArena Expert15161113
SimpleQA Verified41%—
ARC (AI2) Challenge—82.8%
MMLU—68.8%
OpenBookQA—82.6%
TriviaQA—67.7%

Multilingual GLM-5.3 leads

GLM-5.3: 55.7 (#28), Llama 3-8B: 30.8 (#261)

Multilingual benchmarks
BenchmarkGLM-5.3Llama 3-8B
LMArena Non-English14571098
LMArena Chinese15281076
LMArena French14991159
LMArena German14991104
LMArena Japanese1453967
LMArena Korean14721004
LMArena Russian14631109
LMArena Spanish14601173

Instruction Following GLM-5.3 leads

GLM-5.3: 77.5 (#23), Llama 3-8B: 58.4 (#260)

Instruction Following benchmarks
BenchmarkGLM-5.3Llama 3-8B
LMArena Instruction Following14771127

Long Context GLM-5.3 leads

GLM-5.3: 45.4 (#41), Llama 3-8B: 34.2 (#251)

Long Context benchmarks
BenchmarkGLM-5.3Llama 3-8B
LMArena Longer Query14821128

Writing & Preference GLM-5.3 leads

GLM-5.3: 75.7 (#6), Llama 3-8B: 37.5 (#256)

Writing & Preference benchmarks
BenchmarkGLM-5.3Llama 3-8B
LMArena Text14711166
LMArena Creative Writing14571150
LMArena Multi-Turn14721152
EQ-Bench Creative Writing2075—

Frequently asked questions

Is GLM-5.3 better than Llama 3-8B?

GLM-5.3 is the stronger model overall, scoring 54.8 to 25.5 on the Noometry Index.

Is GLM-5.3 or Llama 3-8B better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.5 versus 31.0 in the Noometry coding category.

How many benchmarks do GLM-5.3 and Llama 3-8B share?

22 benchmarks have published results for both models. GLM-5.3 has 42 scored results on Noometry and Llama 3-8B has 34.

Related comparisons

Go deeper