Model comparison

Grok 4.20 Multi-Agent vs Qwen1.5-14B

Grok 4.20 Multi-Agent is the stronger model overall, scoring 45.5 to 32.1 on the Noometry Index.

Last verified . 16 shared benchmarks.

Grok 4.20 Multi-Agent xAI

45.5

Rank #62 Confirmed

Qwen1.5-14B Alibaba (Qwen)

32.1

Rank #250 Confirmed

Summary

  • They share 16 benchmarks with published results for both. Grok 4.20 Multi-Agent scores higher in 8 categories and Qwen1.5-14B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where Grok 4.20 Multi-Agent leads 64.1 to 33.7.
  • Qwen1.5-14B has downloadable open weights; the other is API-only.

Side by side

Grok 4.20 Multi-Agent and Qwen1.5-14B specifications
Grok 4.20 Multi-AgentQwen1.5-14B
ProviderxAIAlibaba (Qwen)
Noometry Index45.532.1
Released2026-03-092024-02-04
WeightsProprietaryOpen
Context window1M—
Max output30K—
Input $ / M tokens$1.25—
Output $ / M tokens$2.50—
Results tracked2017

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Category by category

Coding Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 42.4 (#91), Qwen1.5-14B: 32.5 (#259)

Coding benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-14B
LMArena Coding14581138

Agentic & Tool Use Not comparable

Grok 4.20 Multi-Agent: —, Qwen1.5-14B: —

Agentic & Tool Use benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-14B
LMArena Search1204—

Reasoning Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 42.4 (#44), Qwen1.5-14B: 20.5 (#217)

Reasoning benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-14B
LMArena Hard Prompts14481113
NYT Connections (extended)89.6%—

Math Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 36.6 (#106), Qwen1.5-14B: 29.9 (#214)

Math benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-14B
LMArena Math14411125

Knowledge Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 39.7 (#116), Qwen1.5-14B: 29.3 (#230)

Knowledge benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-14B
LMArena Expert14451094
MMLU—68.6%

Multimodal Not comparable

Grok 4.20 Multi-Agent: 39.8 (#44), Qwen1.5-14B: —

Multimodal benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-14B
LMArena Vision1259—

Multilingual Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 54.6 (#40), Qwen1.5-14B: 30.8 (#257)

Multilingual benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-14B
LMArena Non-English14401095
LMArena Chinese14751147
LMArena French14671115
LMArena German14561043
LMArena Japanese14051019
LMArena Russian14571046
LMArena Spanish14471085
LMArena Korean1416—

Instruction Following Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 75.0 (#80), Qwen1.5-14B: 57.1 (#266)

Instruction Following benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-14B
LMArena Instruction Following14201102

Long Context Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 43.7 (#84), Qwen1.5-14B: 33.7 (#252)

Long Context benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-14B
LMArena Longer Query14301113

Writing & Preference Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 64.1 (#57), Qwen1.5-14B: 33.7 (#270)

Writing & Preference benchmarks
BenchmarkGrok 4.20 Multi-AgentQwen1.5-14B
LMArena Text14501128
LMArena Creative Writing14351091
LMArena Multi-Turn14511110

Frequently asked questions

Is Grok 4.20 Multi-Agent better than Qwen1.5-14B?

Grok 4.20 Multi-Agent is the stronger model overall, scoring 45.5 to 32.1 on the Noometry Index.

Is Grok 4.20 Multi-Agent or Qwen1.5-14B better for coding?

Grok 4.20 Multi-Agent scores higher on coding benchmarks: 42.4 versus 32.5 in the Noometry coding category.

How many benchmarks do Grok 4.20 Multi-Agent and Qwen1.5-14B share?

16 benchmarks have published results for both models. Grok 4.20 Multi-Agent has 20 scored results on Noometry and Qwen1.5-14B has 17.

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