Noometry

Model comparison

Grok 4.20 Multi-Agent vs Llama 13b

Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 24.4 on the Noometry Index.

Last verified . 8 shared benchmarks.

Grok 4.20 Multi-Agent xAI

46.2

Rank #65 Confirmed

Llama 13b Meta

24.4

Rank #348 Confirmed

Summary

  • They share 8 benchmarks with published results for both. Grok 4.20 Multi-Agent scores higher in 6 categories and Llama 13b in 0 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where Grok 4.20 Multi-Agent leads 64.0 to 13.8.
  • Llama 13b has downloadable open weights; the other is API-only.

Side by side

Grok 4.20 Multi-AgentLlama 13b
ProviderxAIMeta
Noometry Index46.224.4
Released2026-03-092023-02-24
WeightsProprietaryOpen
Context window1M—
Max output30K—
Input $ / M tokens$1.25—
Output $ / M tokens$2.50—
Results tracked2021

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Category by category

Coding Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 43.0 (#92), Llama 13b: 21.4 (#337)

BenchmarkGrok 4.20 Multi-AgentLlama 13b
LMArena Coding1457683

Agentic & Tool Use Not comparable

Grok 4.20 Multi-Agent: —, Llama 13b: —

BenchmarkGrok 4.20 Multi-AgentLlama 13b
LMArena Search1204—

Reasoning Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 43.9 (#48), Llama 13b: 14.0 (#329)

BenchmarkGrok 4.20 Multi-AgentLlama 13b
LMArena Hard Prompts1448728
NYT Connections (extended)89.6%—
BIG-Bench Hard—37.9%
Epoch Capabilities Index—100.58
HellaSwag—79.2%
LAMBADA—75.2%
PIQA—80.1%
WinoGrande—73%

Math Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 39.4 (#104), Llama 13b: 26.7 (#256)

BenchmarkGrok 4.20 Multi-AgentLlama 13b
LMArena Math1442838
GSM8K—20.6%

Knowledge Not comparable

Grok 4.20 Multi-Agent: 40.4 (#119), Llama 13b: —

BenchmarkGrok 4.20 Multi-AgentLlama 13b
LMArena Expert1445—
ARC (AI2) Challenge—52.7%
BoolQ—78.7%
MMLU—47.7%
OpenBookQA—56.4%
TriviaQA—77.9%

Multimodal Not comparable

Grok 4.20 Multi-Agent: 40.5 (#48), Llama 13b: —

BenchmarkGrok 4.20 Multi-AgentLlama 13b
LMArena Vision1259—
ScienceQA—43.3%

Multilingual Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 54.4 (#43), Llama 13b: 16.6 (#297)

BenchmarkGrok 4.20 Multi-AgentLlama 13b
LMArena Non-English1440819
LMArena Chinese1475—
LMArena French1466—
LMArena German1456—
LMArena Japanese1405—
LMArena Korean1416—
LMArena Russian1457—
LMArena Spanish1447—

Instruction Following Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 74.8 (#84), Llama 13b: 36.7 (#305)

BenchmarkGrok 4.20 Multi-AgentLlama 13b
LMArena Instruction Following1420781

Long Context Not comparable

Grok 4.20 Multi-Agent: 43.7 (#88), Llama 13b: —

BenchmarkGrok 4.20 Multi-AgentLlama 13b
LMArena Longer Query1431—

Writing & Preference Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 64.0 (#59), Llama 13b: 13.8 (#312)

BenchmarkGrok 4.20 Multi-AgentLlama 13b
LMArena Text1450834
LMArena Creative Writing1436794
LMArena Multi-Turn1452753

Frequently asked questions

Is Grok 4.20 Multi-Agent better than Llama 13b?

Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 24.4 on the Noometry Index.

Is Grok 4.20 Multi-Agent or Llama 13b better for coding?

Grok 4.20 Multi-Agent scores higher on coding benchmarks: 43.0 versus 21.4 in the Noometry coding category.

How many benchmarks do Grok 4.20 Multi-Agent and Llama 13b share?

8 benchmarks have published results for both models. Grok 4.20 Multi-Agent has 20 scored results on Noometry and Llama 13b has 21.

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