Noometry

Model comparison

Grok 4.20 Multi-Agent vs Llama 2-7B

Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 29.1 on the Noometry Index.

Last verified . 15 shared benchmarks.

Grok 4.20 Multi-Agent xAI

46.2

Rank #65 Confirmed

Llama 2-7B Meta

29.1

Rank #317 Confirmed

Summary

  • They share 15 benchmarks with published results for both. Grok 4.20 Multi-Agent scores higher in 8 categories and Llama 2-7B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where Grok 4.20 Multi-Agent leads 64.0 to 28.0.
  • Llama 2-7B has downloadable open weights; the other is API-only.

Side by side

Grok 4.20 Multi-AgentLlama 2-7B
ProviderxAIMeta
Noometry Index46.229.1
Released2026-03-092023-07-18
WeightsProprietaryOpen
Context window1M—
Max output30K—
Input $ / M tokens$1.25—
Output $ / M tokens$2.50—
Results tracked2029

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Category by category

Coding Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 43.0 (#92), Llama 2-7B: 29.2 (#307)

BenchmarkGrok 4.20 Multi-AgentLlama 2-7B
LMArena Coding14571002

Agentic & Tool Use Not comparable

Grok 4.20 Multi-Agent: —, Llama 2-7B: —

BenchmarkGrok 4.20 Multi-AgentLlama 2-7B
LMArena Search1204—

Reasoning Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 43.9 (#48), Llama 2-7B: 15.7 (#312)

BenchmarkGrok 4.20 Multi-AgentLlama 2-7B
LMArena Hard Prompts14481009
NYT Connections (extended)89.6%—
Chess Puzzles—0%
BIG-Bench Hard—39.2%
Epoch Capabilities Index—99.06
HellaSwag—77.2%
LAMBADA—73.3%
PIQA—78.8%
WinoGrande—69.2%

Math Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 39.4 (#104), Llama 2-7B: 30.7 (#233)

BenchmarkGrok 4.20 Multi-AgentLlama 2-7B
LMArena Math14421042
GSM8K—16.7%

Knowledge Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 40.4 (#119), Llama 2-7B: 28.2 (#248)

BenchmarkGrok 4.20 Multi-AgentLlama 2-7B
LMArena Expert14451036
ARC (AI2) Challenge—45.9%
BoolQ—77.9%
MMLU—45.8%
OpenBookQA—58.6%
TriviaQA—73.7%

Multimodal Not comparable

Grok 4.20 Multi-Agent: 40.5 (#48), Llama 2-7B: —

BenchmarkGrok 4.20 Multi-AgentLlama 2-7B
LMArena Vision1259—
ScienceQA—43.1%

Multilingual Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 54.4 (#43), Llama 2-7B: 23.8 (#293)

BenchmarkGrok 4.20 Multi-AgentLlama 2-7B
LMArena Non-English1440973
LMArena Chinese1475973
LMArena French1466970
LMArena German1456978
LMArena Russian1457995
LMArena Spanish14471007
LMArena Japanese1405—
LMArena Korean1416—

Instruction Following Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 74.8 (#84), Llama 2-7B: 50.8 (#298)

BenchmarkGrok 4.20 Multi-AgentLlama 2-7B
LMArena Instruction Following14201006

Long Context Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 43.7 (#88), Llama 2-7B: 30.4 (#287)

BenchmarkGrok 4.20 Multi-AgentLlama 2-7B
LMArena Longer Query1431999

Writing & Preference Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 64.0 (#59), Llama 2-7B: 28.0 (#298)

BenchmarkGrok 4.20 Multi-AgentLlama 2-7B
LMArena Text14501053
LMArena Creative Writing14361033
LMArena Multi-Turn14521029

Frequently asked questions

Is Grok 4.20 Multi-Agent better than Llama 2-7B?

Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 29.1 on the Noometry Index.

Is Grok 4.20 Multi-Agent or Llama 2-7B better for coding?

Grok 4.20 Multi-Agent scores higher on coding benchmarks: 43.0 versus 29.2 in the Noometry coding category.

How many benchmarks do Grok 4.20 Multi-Agent and Llama 2-7B share?

15 benchmarks have published results for both models. Grok 4.20 Multi-Agent has 20 scored results on Noometry and Llama 2-7B has 29.

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