Noometry

Model comparison

Grok 4.20 Multi-Agent vs Llama 3-70B

Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 28.8 on the Noometry Index.

Last verified . 17 shared benchmarks.

Grok 4.20 Multi-Agent xAI

46.2

Rank #65 Confirmed

Llama 3-70B Meta

28.8

Rank #323 Confirmed

Summary

  • They share 17 benchmarks with published results for both. Grok 4.20 Multi-Agent scores higher in 8 categories and Llama 3-70B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where Grok 4.20 Multi-Agent leads 39.4 to 12.8.
  • Llama 3-70B has downloadable open weights; the other is API-only.

Side by side

Grok 4.20 Multi-AgentLlama 3-70B
ProviderxAIMeta
Noometry Index46.228.8
Released2026-03-092024-04-18
WeightsProprietaryOpen
Context window1M—
Max output30K—
Input $ / M tokens$1.25—
Output $ / M tokens$2.50—
Results tracked2031

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Category by category

Coding Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 43.0 (#92), Llama 3-70B: 35.8 (#218)

BenchmarkGrok 4.20 Multi-AgentLlama 3-70B
LMArena Coding14571206
BigCodeBench Instruct—43.6%
BigCodeBench Complete—54.5%
HumanEval+—72%
MBPP+—69%

Agentic & Tool Use Not comparable

Grok 4.20 Multi-Agent: —, Llama 3-70B: 21.1 (#139)

BenchmarkGrok 4.20 Multi-AgentLlama 3-70B
Cybench—5%
LMArena Search1204—

Reasoning Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 43.9 (#48), Llama 3-70B: 18.0 (#288)

BenchmarkGrok 4.20 Multi-AgentLlama 3-70B
LMArena Hard Prompts14481195
Kagi LLM Benchmark—35.1%
NYT Connections (extended)89.6%—
DTBench—54.2%
Epoch Capabilities Index—122.93
ForecastBench—57.1
WinoGrande—83.5%

Math Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 39.4 (#104), Llama 3-70B: 12.8 (#305)

BenchmarkGrok 4.20 Multi-AgentLlama 3-70B
LMArena Math14421218
OTIS Mock AIME 2024-2025—4.3%
MATH Level 5—22.6%

Knowledge Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 40.4 (#119), Llama 3-70B: 20.8 (#277)

BenchmarkGrok 4.20 Multi-AgentLlama 3-70B
LMArena Expert14451149
GPQA Diamond—40.6%
MMLU—79.3%

Multimodal Not comparable

Grok 4.20 Multi-Agent: 40.5 (#48), Llama 3-70B: —

BenchmarkGrok 4.20 Multi-AgentLlama 3-70B
LMArena Vision1259—

Multilingual Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 54.4 (#43), Llama 3-70B: 33.6 (#251)

BenchmarkGrok 4.20 Multi-AgentLlama 3-70B
LMArena Non-English14401142
LMArena Chinese14751114
LMArena French14661232
LMArena German14561169
LMArena Japanese14051017
LMArena Korean14161017
LMArena Russian14571159
LMArena Spanish14471241

Instruction Following Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 74.8 (#84), Llama 3-70B: 62.5 (#238)

BenchmarkGrok 4.20 Multi-AgentLlama 3-70B
LMArena Instruction Following14201194

Long Context Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 43.7 (#88), Llama 3-70B: 35.6 (#240)

BenchmarkGrok 4.20 Multi-AgentLlama 3-70B
LMArena Longer Query14311174

Writing & Preference Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 64.0 (#59), Llama 3-70B: 42.8 (#231)

BenchmarkGrok 4.20 Multi-AgentLlama 3-70B
LMArena Text14501221
LMArena Creative Writing14361210
LMArena Multi-Turn14521223

Frequently asked questions

Is Grok 4.20 Multi-Agent better than Llama 3-70B?

Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 28.8 on the Noometry Index.

Is Grok 4.20 Multi-Agent or Llama 3-70B better for coding?

Grok 4.20 Multi-Agent scores higher on coding benchmarks: 43.0 versus 35.8 in the Noometry coding category.

How many benchmarks do Grok 4.20 Multi-Agent and Llama 3-70B share?

17 benchmarks have published results for both models. Grok 4.20 Multi-Agent has 20 scored results on Noometry and Llama 3-70B has 31.

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