Model comparison

Grok 4.20 Multi-Agent vs Qwen2-72B

Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 30.0 on the Noometry Index.

Last verified . 17 shared benchmarks.

Grok 4.20 Multi-Agent xAI

46.2

Rank #65 Confirmed

Qwen2-72B Alibaba (Qwen)

30.0

Rank #300 Confirmed

Summary

  • They share 17 benchmarks with published results for both. Grok 4.20 Multi-Agent scores higher in 8 categories and Qwen2-72B 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 40.8.
  • Qwen2-72B has downloadable open weights; the other is API-only.

Side by side

Grok 4.20 Multi-Agent and Qwen2-72B specifications
Grok 4.20 Multi-AgentQwen2-72B
ProviderxAIAlibaba (Qwen)
Noometry Index46.230.0
Released2026-03-092024-06-07
WeightsProprietaryOpen
Context window1M—
Max output30K—
Input $ / M tokens$1.25—
Output $ / M tokens$2.50—
Results tracked2026

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Category by category

Coding Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 43.0 (#92), Qwen2-72B: 29.1 (#310)

Coding benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen2-72B
LMArena Coding14571196
WeirdML—11.3%
BigCodeBench Instruct—38.5%
BigCodeBench Complete—54%

Agentic & Tool Use Not comparable

Grok 4.20 Multi-Agent: —, Qwen2-72B: 17.0 (#146)

Agentic & Tool Use benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen2-72B
TheAgentCompany—1.1%
LMArena Search1204—
METR Time Horizons—29.9%

Reasoning Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 43.9 (#48), Qwen2-72B: 23.2 (#181)

Reasoning benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen2-72B
LMArena Hard Prompts14481191
NYT Connections (extended)89.6%—
Epoch Capabilities Index—125.28

Math Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 39.4 (#104), Qwen2-72B: 30.2 (#236)

Math benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen2-72B
LMArena Math14421235
MATH Level 5—39.1%

Knowledge Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 40.4 (#119), Qwen2-72B: 21.2 (#275)

Knowledge benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen2-72B
LMArena Expert14451171
GPQA Diamond—40.8%
MMLU—82.4%

Multimodal Not comparable

Grok 4.20 Multi-Agent: 40.5 (#48), Qwen2-72B: —

Multimodal benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen2-72B
LMArena Vision1259—

Multilingual Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 54.4 (#43), Qwen2-72B: 35.9 (#244)

Multilingual benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen2-72B
LMArena Non-English14401176
LMArena Chinese14751240
LMArena French14661170
LMArena German14561151
LMArena Japanese14051111
LMArena Korean14161083
LMArena Russian14571169
LMArena Spanish14471169

Instruction Following Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 74.8 (#84), Qwen2-72B: 61.7 (#241)

Instruction Following benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen2-72B
LMArena Instruction Following14201181

Long Context Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 43.7 (#88), Qwen2-72B: 36.1 (#235)

Long Context benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen2-72B
LMArena Longer Query14311192

Writing & Preference Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 64.0 (#59), Qwen2-72B: 40.8 (#241)

Writing & Preference benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen2-72B
LMArena Text14501203
LMArena Creative Writing14361181
LMArena Multi-Turn14521196

Frequently asked questions

Is Grok 4.20 Multi-Agent better than Qwen2-72B?

Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 30.0 on the Noometry Index.

Is Grok 4.20 Multi-Agent or Qwen2-72B better for coding?

Grok 4.20 Multi-Agent scores higher on coding benchmarks: 43.0 versus 29.1 in the Noometry coding category.

How many benchmarks do Grok 4.20 Multi-Agent and Qwen2-72B share?

17 benchmarks have published results for both models. Grok 4.20 Multi-Agent has 20 scored results on Noometry and Qwen2-72B has 26.

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