Model comparison

Qwen-14B vs Qwen3 235B-A22B

Qwen3 235B-A22B is the stronger model overall, scoring 43.5 to 31.4 on the Noometry Index.

Last verified . 11 shared benchmarks.

Qwen-14B Alibaba (Qwen)

31.4

Rank #275 Confirmed

Qwen3 235B-A22B Alibaba (Qwen)

43.5

Rank #91 Confirmed

Summary

  • They share 11 benchmarks with published results for both. Qwen-14B scores higher in 1 category and Qwen3 235B-A22B in 6 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where Qwen3 235B-A22B leads 59.6 to 27.6.

Side by side

Qwen-14B and Qwen3 235B-A22B specifications
Qwen-14BQwen3 235B-A22B
ProviderAlibaba (Qwen)Alibaba (Qwen)
Noometry Index31.443.5
Released2023-09-242025-04
WeightsOpenOpen
Context window—131K
Max output—16K
Input $ / M tokens—$0.70
Output $ / M tokens—$2.80
Results tracked1849

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Category by category

Coding Qwen3 235B-A22B leads

Qwen-14B: 31.2 (#288), Qwen3 235B-A22B: 44.3 (#75)

Coding benchmarks
BenchmarkQwen-14BQwen3 235B-A22B
LMArena Coding10711445
Aider Polyglot—59.6%
SciCode—42.4%
WeirdML—41%

Agentic & Tool Use Not comparable

Qwen-14B: —, Qwen3 235B-A22B: 33.9 (#51)

Agentic & Tool Use benchmarks
BenchmarkQwen-14BQwen3 235B-A22B
Berkeley Function Calling Leaderboard—52.1%
Vending-Bench 2—-11.34

Reasoning Qwen-14B leads

Qwen-14B: 19.6 (#257), Qwen3 235B-A22B: 15.7 (#311)

Reasoning benchmarks
BenchmarkQwen-14BQwen3 235B-A22B
LMArena Hard Prompts10271433
Epoch Capabilities Index113.03143.85
ARC-AGI-2—1.3%
SimpleBench—31%
Kagi LLM Benchmark—69.4%
ARC-AGI-1—11%
CritPt—0%
Chess Puzzles—12%
Mystery Game Puzzles—9%
DTBench—80.3%
LMCA—29.3%
BIG-Bench Hard55%—
ForecastBench—59.7
LAMBADA71.1%—
PIQA79.9%—

Math Qwen3 235B-A22B leads

Qwen-14B: 31.2 (#227), Qwen3 235B-A22B: 50.4 (#57)

Math benchmarks
BenchmarkQwen-14BQwen3 235B-A22B
LMArena Math10681432
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%
GSM8K61.3%—

Knowledge Not comparable

Qwen-14B: —, Qwen3 235B-A22B: 49.6 (#73)

Knowledge benchmarks
BenchmarkQwen-14BQwen3 235B-A22B
GPQA Diamond—80.1%
SimpleQA Verified—40.4%
MMLU-Pro—84.4%
Confabulations—15.6%
Vectara Hallucination Rate—9.3%
GPQA (HELM)—72.7%
LMArena Expert—1463
ARC (AI2) Challenge84.4%—
BoolQ86.2%—
MMLU66.3%—

Multilingual Qwen3 235B-A22B leads

Qwen-14B: 27.5 (#275), Qwen3 235B-A22B: 52.3 (#89)

Multilingual benchmarks
BenchmarkQwen-14BQwen3 235B-A22B
LMArena Non-English10411409
LMArena Chinese10771481
LMArena French—1445
LMArena German—1433
LMArena Japanese—1399
LMArena Korean—1391
LMArena Russian—1411
LMArena Spanish—1430

Instruction Following Qwen3 235B-A22B leads

Qwen-14B: 52.4 (#289), Qwen3 235B-A22B: 72.6 (#136)

Instruction Following benchmarks
BenchmarkQwen-14BQwen3 235B-A22B
LMArena Instruction Following10311408
IFEval—83.5%

Long Context Qwen3 235B-A22B leads

Qwen-14B: 31.3 (#280), Qwen3 235B-A22B: 46.1 (#26)

Long Context benchmarks
BenchmarkQwen-14BQwen3 235B-A22B
LMArena Longer Query10281426
Fiction.LiveBench—75%

Writing & Preference Qwen3 235B-A22B leads

Qwen-14B: 27.6 (#299), Qwen3 235B-A22B: 59.6 (#108)

Writing & Preference benchmarks
BenchmarkQwen-14BQwen3 235B-A22B
LMArena Text10511419
LMArena Creative Writing10281384
LMArena Multi-Turn10221432
Short-Story Creative Writing—83%
EQ-Bench Creative Writing—1366
WildBench—86.6%

Frequently asked questions

Is Qwen-14B better than Qwen3 235B-A22B?

Qwen3 235B-A22B is the stronger model overall, scoring 43.5 to 31.4 on the Noometry Index.

Is Qwen-14B or Qwen3 235B-A22B better for coding?

Qwen3 235B-A22B scores higher on coding benchmarks: 44.3 versus 31.2 in the Noometry coding category.

How many benchmarks do Qwen-14B and Qwen3 235B-A22B share?

11 benchmarks have published results for both models. Qwen-14B has 18 scored results on Noometry and Qwen3 235B-A22B has 49.

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