Model comparison

Grok 4.20 Multi-Agent vs Qwen1.5-72B

Grok 4.20 Multi-Agent is the stronger model overall, scoring 45.5 to 30.3 on the Noometry Index.

Last verified . 17 shared benchmarks.

Grok 4.20 Multi-Agent xAI

45.5

Rank #62 Confirmed

Qwen1.5-72B Alibaba (Qwen)

30.3

Rank #282 Confirmed

Summary

  • They share 17 benchmarks with published results for both. Grok 4.20 Multi-Agent scores higher in 8 categories and Qwen1.5-72B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Grok 4.20 Multi-Agent leads 39.7 to 11.5.
  • Qwen1.5-72B has downloadable open weights; the other is API-only.

Side by side

Grok 4.20 Multi-Agent and Qwen1.5-72B specifications
Grok 4.20 Multi-AgentQwen1.5-72B
ProviderxAIAlibaba (Qwen)
Noometry Index45.530.3
Released2026-03-092024-02-04
WeightsProprietaryOpen
Context window1M—
Max output30K—
Input $ / M tokens$1.25—
Output $ / M tokens$2.50—
Results tracked2022

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Category by category

Coding Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 42.4 (#91), Qwen1.5-72B: 31.4 (#272)

Coding benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-72B
LMArena Coding14581166
BigCodeBench Instruct—33.2%
BigCodeBench Complete—40.3%
HumanEval+—59.1%
MBPP+—61.6%

Agentic & Tool Use Not comparable

Grok 4.20 Multi-Agent: —, Qwen1.5-72B: —

Agentic & Tool Use benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-72B
LMArena Search1204—

Reasoning Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 42.4 (#44), Qwen1.5-72B: 21.2 (#201)

Reasoning benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-72B
LMArena Hard Prompts14481148
NYT Connections (extended)89.6%—

Math Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 36.6 (#106), Qwen1.5-72B: 30.7 (#205)

Math benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-72B
LMArena Math14411164

Knowledge Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 39.7 (#116), Qwen1.5-72B: 11.5 (#295)

Knowledge benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-72B
LMArena Expert14451136
GPQA Diamond—28.8%

Multimodal Not comparable

Grok 4.20 Multi-Agent: 39.8 (#44), Qwen1.5-72B: —

Multimodal benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-72B
LMArena Vision1259—

Multilingual Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 54.6 (#40), Qwen1.5-72B: 33.4 (#248)

Multilingual benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-72B
LMArena Non-English14401135
LMArena Chinese14751186
LMArena French14671158
LMArena German14561084
LMArena Japanese14051061
LMArena Korean14161049
LMArena Russian14571104
LMArena Spanish14471110

Instruction Following Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 75.0 (#80), Qwen1.5-72B: 59.6 (#251)

Instruction Following benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-72B
LMArena Instruction Following14201142

Long Context Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 43.7 (#84), Qwen1.5-72B: 35.0 (#238)

Long Context benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-72B
LMArena Longer Query14301157

Writing & Preference Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 64.1 (#57), Qwen1.5-72B: 37.4 (#253)

Writing & Preference benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-72B
LMArena Text14501166
LMArena Creative Writing14351137
LMArena Multi-Turn14511160

Frequently asked questions

Is Grok 4.20 Multi-Agent better than Qwen1.5-72B?

Grok 4.20 Multi-Agent is the stronger model overall, scoring 45.5 to 30.3 on the Noometry Index.

Is Grok 4.20 Multi-Agent or Qwen1.5-72B better for coding?

Grok 4.20 Multi-Agent scores higher on coding benchmarks: 42.4 versus 31.4 in the Noometry coding category.

How many benchmarks do Grok 4.20 Multi-Agent and Qwen1.5-72B share?

17 benchmarks have published results for both models. Grok 4.20 Multi-Agent has 20 scored results on Noometry and Qwen1.5-72B has 22.

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