Noometry

Model comparison

Grok 4.20 Multi-Agent vs Llama 3-8B

Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 25.5 on the Noometry Index.

Last verified . 17 shared benchmarks.

Grok 4.20 Multi-Agent xAI

46.2

Rank #65 Confirmed

Llama 3-8B Meta

25.5

Rank #344 Confirmed

Summary

  • They share 17 benchmarks with published results for both. Grok 4.20 Multi-Agent 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 Grok 4.20 Multi-Agent leads 40.4 to 7.8.
  • Llama 3-8B has downloadable open weights; the other is API-only.

Side by side

Grok 4.20 Multi-AgentLlama 3-8B
ProviderxAIMeta
Noometry Index46.225.5
Released2026-03-092024-04-18
WeightsProprietaryOpen
Context window1M—
Max output30K—
Input $ / M tokens$1.25—
Output $ / M tokens$2.50—
Results tracked2034

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

Category by category

Coding Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 43.0 (#92), Llama 3-8B: 31.0 (#289)

BenchmarkGrok 4.20 Multi-AgentLlama 3-8B
LMArena Coding14571152
BigCodeBench Instruct—31.9%
BigCodeBench Complete—36.9%
HumanEval+—56.7%
MBPP+—54.8%

Agentic & Tool Use Not comparable

Grok 4.20 Multi-Agent: —, Llama 3-8B: —

BenchmarkGrok 4.20 Multi-AgentLlama 3-8B
LMArena Search1204—

Reasoning Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 43.9 (#48), Llama 3-8B: 14.3 (#326)

BenchmarkGrok 4.20 Multi-AgentLlama 3-8B
LMArena Hard Prompts14481133
NYT Connections (extended)89.6%—
Chess Puzzles—0%
DTBench—43.9%
Adversarial NLI—57.3%
Epoch Capabilities Index—116.45
ForecastBench—58.6
WinoGrande—75.7%

Math Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 39.4 (#104), Llama 3-8B: 8.8 (#323)

BenchmarkGrok 4.20 Multi-AgentLlama 3-8B
LMArena Math14421151
OTIS Mock AIME 2024-2025—1.9%
MATH Level 5—6.1%

Knowledge Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 40.4 (#119), Llama 3-8B: 7.8 (#308)

BenchmarkGrok 4.20 Multi-AgentLlama 3-8B
LMArena Expert14451113
GPQA Diamond—26.1%
ARC (AI2) Challenge—82.8%
MMLU—68.8%
OpenBookQA—82.6%
TriviaQA—67.7%

Multimodal Not comparable

Grok 4.20 Multi-Agent: 40.5 (#48), Llama 3-8B: —

BenchmarkGrok 4.20 Multi-AgentLlama 3-8B
LMArena Vision1259—

Multilingual Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 54.4 (#43), Llama 3-8B: 30.8 (#261)

BenchmarkGrok 4.20 Multi-AgentLlama 3-8B
LMArena Non-English14401098
LMArena Chinese14751076
LMArena French14661159
LMArena German14561104
LMArena Japanese1405967
LMArena Korean14161004
LMArena Russian14571109
LMArena Spanish14471173

Instruction Following Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 74.8 (#84), Llama 3-8B: 58.4 (#260)

BenchmarkGrok 4.20 Multi-AgentLlama 3-8B
LMArena Instruction Following14201127

Long Context Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 43.7 (#88), Llama 3-8B: 34.2 (#251)

BenchmarkGrok 4.20 Multi-AgentLlama 3-8B
LMArena Longer Query14311128

Writing & Preference Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 64.0 (#59), Llama 3-8B: 37.5 (#256)

BenchmarkGrok 4.20 Multi-AgentLlama 3-8B
LMArena Text14501166
LMArena Creative Writing14361150
LMArena Multi-Turn14521152

Frequently asked questions

Is Grok 4.20 Multi-Agent better than Llama 3-8B?

Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 25.5 on the Noometry Index.

Is Grok 4.20 Multi-Agent or Llama 3-8B better for coding?

Grok 4.20 Multi-Agent scores higher on coding benchmarks: 43.0 versus 31.0 in the Noometry coding category.

How many benchmarks do Grok 4.20 Multi-Agent and Llama 3-8B share?

17 benchmarks have published results for both models. Grok 4.20 Multi-Agent has 20 scored results on Noometry and Llama 3-8B has 34.

Related comparisons

Go deeper