Noometry

Model comparison

Grok 4.20 Multi-Agent vs Qwen3 235B-A22B

Grok 4.20 Multi-Agent is the stronger model overall, scoring 45.5 to 43.2 on the Noometry Index.

Last verified . 17 shared benchmarks.

Grok 4.20 Multi-Agent xAI

45.5

Rank #62 Confirmed

Qwen3 235B-A22B Alibaba (Qwen)

43.2

Rank #83 Confirmed

Summary

  • They share 17 benchmarks with published results for both. Grok 4.20 Multi-Agent scores higher in 4 categories and Qwen3 235B-A22B in 4 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Grok 4.20 Multi-Agent leads 42.4 to 15.8.
  • Qwen3 235B-A22B is cheaper at $0.70 / $2.80 per million input/output tokens, against $1.25 / $2.50 for Grok 4.20 Multi-Agent.
  • Grok 4.20 Multi-Agent accepts more context: 1M tokens versus 131K.
  • Qwen3 235B-A22B has downloadable open weights; the other is API-only.

Side by side

Grok 4.20 Multi-AgentQwen3 235B-A22B
ProviderxAIAlibaba (Qwen)
Noometry Index45.543.2
Released2026-03-092025-04
WeightsProprietaryOpen
Context window1M131K
Max output30K16K
Input $ / M tokens$1.25$0.70
Output $ / M tokens$2.50$2.80
Results tracked2049

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Category by category

Coding Qwen3 235B-A22B leads

Grok 4.20 Multi-Agent: 42.4 (#91), Qwen3 235B-A22B: 43.8 (#72)

BenchmarkGrok 4.20 Multi-AgentQwen3 235B-A22B
LMArena Coding14581445
Aider Polyglot—59.6%
SciCode—42.4%
WeirdML—41%

Agentic & Tool Use Not comparable

Grok 4.20 Multi-Agent: —, Qwen3 235B-A22B: 33.7 (#48)

BenchmarkGrok 4.20 Multi-AgentQwen3 235B-A22B
Berkeley Function Calling Leaderboard—52.1%
LMArena Search1204—
Vending-Bench 2—-11.34

Reasoning Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 42.4 (#44), Qwen3 235B-A22B: 15.8 (#302)

BenchmarkGrok 4.20 Multi-AgentQwen3 235B-A22B
LMArena Hard Prompts14481433
ARC-AGI-2—1.3%
SimpleBench—31%
Kagi LLM Benchmark—69.4%
NYT Connections (extended)89.6%—
ARC-AGI-1—11%
CritPt—0%
Chess Puzzles—12%
Mystery Game Puzzles—9%
DTBench—80.3%
LMCA—29.3%
Epoch Capabilities Index—143.87
ForecastBench—59.7

Math Qwen3 235B-A22B leads

Grok 4.20 Multi-Agent: 36.6 (#106), Qwen3 235B-A22B: 48.5 (#51)

BenchmarkGrok 4.20 Multi-AgentQwen3 235B-A22B
LMArena Math14411431
OTIS Mock AIME 2024-2025—86.7%
Omni-MATH—71.8%
MATH Level 5—68.9%
FrontierMath (Feb 2025 set)—8.5%
FrontierMath Tier 4 (v1)—0%

Knowledge Qwen3 235B-A22B leads

Grok 4.20 Multi-Agent: 39.7 (#116), Qwen3 235B-A22B: 49.5 (#67)

BenchmarkGrok 4.20 Multi-AgentQwen3 235B-A22B
LMArena Expert14451460
GPQA Diamond—80.1%
SimpleQA Verified—40.4%
MMLU-Pro—84.4%
Confabulations—15.6%
Vectara Hallucination Rate—9.3%
GPQA (HELM)—72.7%

Multimodal Not comparable

Grok 4.20 Multi-Agent: 39.8 (#44), Qwen3 235B-A22B: —

BenchmarkGrok 4.20 Multi-AgentQwen3 235B-A22B
LMArena Vision1259—

Multilingual Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 54.6 (#40), Qwen3 235B-A22B: 52.5 (#84)

BenchmarkGrok 4.20 Multi-AgentQwen3 235B-A22B
LMArena Non-English14401410
LMArena Chinese14751481
LMArena French14671445
LMArena German14561432
LMArena Japanese14051400
LMArena Korean14161391
LMArena Russian14571411
LMArena Spanish14471429

Instruction Following Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 75.0 (#80), Qwen3 235B-A22B: 72.8 (#132)

BenchmarkGrok 4.20 Multi-AgentQwen3 235B-A22B
LMArena Instruction Following14201408
IFEval—83.5%

Long Context Qwen3 235B-A22B leads

Grok 4.20 Multi-Agent: 43.7 (#84), Qwen3 235B-A22B: 46.1 (#25)

BenchmarkGrok 4.20 Multi-AgentQwen3 235B-A22B
LMArena Longer Query14301426
Fiction.LiveBench—75%

Writing & Preference Grok 4.20 Multi-Agent leads

Grok 4.20 Multi-Agent: 64.1 (#57), Qwen3 235B-A22B: 59.8 (#103)

BenchmarkGrok 4.20 Multi-AgentQwen3 235B-A22B
LMArena Text14501419
LMArena Creative Writing14351384
LMArena Multi-Turn14511432
Short-Story Creative Writing—83%
EQ-Bench Creative Writing—1366
WildBench—86.6%

Frequently asked questions

Is Grok 4.20 Multi-Agent better than Qwen3 235B-A22B?

Grok 4.20 Multi-Agent is the stronger model overall, scoring 45.5 to 43.2 on the Noometry Index.

Which is cheaper, Grok 4.20 Multi-Agent or Qwen3 235B-A22B?

Qwen3 235B-A22B is cheaper. It lists at $0.70 per million input tokens and $2.80 per million output tokens; Grok 4.20 Multi-Agent lists at $1.25 and $2.50.

Is Grok 4.20 Multi-Agent or Qwen3 235B-A22B better for coding?

Qwen3 235B-A22B scores higher on coding benchmarks: 43.8 versus 42.4 in the Noometry coding category.

Which has the bigger context window?

Grok 4.20 Multi-Agent does, with 1M tokens against 131K.

How many benchmarks do Grok 4.20 Multi-Agent and Qwen3 235B-A22B share?

17 benchmarks have published results for both models. Grok 4.20 Multi-Agent has 20 scored results on Noometry and Qwen3 235B-A22B has 49.

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