Noometry

Model comparison

GLM-5.3-Flash vs Llama 3-8B

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 25.5 on the Noometry Index.

Last verified . 21 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

Llama 3-8B Meta

25.5

Rank #344 Confirmed

Summary

  • They share 21 benchmarks with published results for both. GLM-5.3-Flash scores higher in 8 categories and Llama 3-8B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-5.3-Flash leads 58.4 to 7.8.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 93.9% for GLM-5.3-Flash and 1.9% for Llama 3-8B.

Side by side

GLM-5.3-FlashLlama 3-8B
ProviderZ.ai (Zhipu)Meta
Noometry Index51.825.5
Released2026-08-202024-04-18
WeightsOpenOpen
Context window1M—
Max output131K—
Input $ / M tokens$0.15—
Output $ / M tokens$0.50—
Results tracked4034

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Category by category

Coding GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#31), Llama 3-8B: 31.0 (#289)

BenchmarkGLM-5.3-FlashLlama 3-8B
LMArena Coding15081152
DeepSWE63.4%—
FrontierCode31.8%—
CursorBench36.8%—
LMArena WebDev1609—
FrontierSWE18.1%—
SciCode51.6%—
BigCodeBench Instruct—31.9%
BigCodeBench Complete—36.9%
ALE-Bench303.55—
HumanEval+—56.7%
MBPP+—54.8%

Agentic & Tool Use Not comparable

GLM-5.3-Flash: 34.2 (#47), Llama 3-8B: —

BenchmarkGLM-5.3-FlashLlama 3-8B
APEX-Agents52.8%—
GDP.pdf14%—

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 48.0 (#42), Llama 3-8B: 14.3 (#326)

BenchmarkGLM-5.3-FlashLlama 3-8B
Chess Puzzles14%0%
LMArena Hard Prompts14911133
Epoch Capabilities Index151.88116.45
ARC-AGI-265.8%—
ARC-AGI-191%—
CritPt15.4%—
Mystery Game Puzzles8%—
DTBench—43.9%
Surface Evolver Bench52.5%—
Adversarial NLI—57.3%
Bench to the Future 30.15—
ForecastBench—58.6
WinoGrande—75.7%

Math GLM-5.3-Flash leads

GLM-5.3-Flash: 53.3 (#47), Llama 3-8B: 8.8 (#323)

BenchmarkGLM-5.3-FlashLlama 3-8B
OTIS Mock AIME 2024-202593.9%1.9%
LMArena Math15001151
FrontierMath (Tiers 1-3)55.8%—
FrontierMath Tier 417.1%—
ProofBench21%—
MATH Level 5—6.1%

Knowledge GLM-5.3-Flash leads

GLM-5.3-Flash: 58.4 (#36), Llama 3-8B: 7.8 (#308)

BenchmarkGLM-5.3-FlashLlama 3-8B
GPQA Diamond90.2%26.1%
LMArena Expert15131113
ARC (AI2) Challenge—82.8%
MMLU—68.8%
OpenBookQA—82.6%
TriviaQA—67.7%

Multimodal Not comparable

GLM-5.3-Flash: 42.8 (#27), Llama 3-8B: —

BenchmarkGLM-5.3-FlashLlama 3-8B
LMArena Vision1296—

Multilingual GLM-5.3-Flash leads

GLM-5.3-Flash: 56.0 (#25), Llama 3-8B: 30.8 (#261)

BenchmarkGLM-5.3-FlashLlama 3-8B
LMArena Non-English14621098
LMArena Chinese15271076
LMArena French14961159
LMArena German14701104
LMArena Japanese1429967
LMArena Korean14461004
LMArena Russian14691109
LMArena Spanish14711173

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.5 (#20), Llama 3-8B: 58.4 (#260)

BenchmarkGLM-5.3-FlashLlama 3-8B
LMArena Instruction Following14781127

Long Context GLM-5.3-Flash leads

GLM-5.3-Flash: 45.4 (#39), Llama 3-8B: 34.2 (#251)

BenchmarkGLM-5.3-FlashLlama 3-8B
LMArena Longer Query14821128

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.3 (#50), Llama 3-8B: 37.5 (#256)

BenchmarkGLM-5.3-FlashLlama 3-8B
LMArena Text14711166
LMArena Creative Writing14421150
LMArena Multi-Turn14671152

Frequently asked questions

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

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 25.5 on the Noometry Index.

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

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 31.0 in the Noometry coding category.

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

21 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and Llama 3-8B has 34.

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