Model comparison

Qwen1.5-14B vs Qwen3.5-Flash

Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 32.7 on the Noometry Index.

Last verified . 16 shared benchmarks.

Qwen1.5-14B Alibaba (Qwen)

32.7

Rank #253 Confirmed

Qwen3.5-Flash Alibaba (Qwen)

42.5

Rank #112 Confirmed

Summary

  • They share 16 benchmarks with published results for both. Qwen1.5-14B scores higher in 0 categories and Qwen3.5-Flash in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where Qwen3.5-Flash leads 57.9 to 33.6.
  • Qwen1.5-14B has downloadable open weights; the other is API-only.

Side by side

Qwen1.5-14B and Qwen3.5-Flash specifications
Qwen1.5-14BQwen3.5-Flash
ProviderAlibaba (Qwen)Alibaba (Qwen)
Noometry Index32.742.5
Released2024-02-042026-02-23
WeightsOpenProprietary
Context window—1M
Max output—66K
Input $ / M tokens—$0.10
Output $ / M tokens—$0.40
Results tracked1732

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Category by category

Coding Qwen3.5-Flash leads

Qwen1.5-14B: 33.1 (#263), Qwen3.5-Flash: 34.2 (#242)

Coding benchmarks
BenchmarkQwen1.5-14BQwen3.5-Flash
LMArena Coding11381412
LMArena WebDev—1244
ALE-Bench—221.8

Agentic & Tool Use Not comparable

Qwen1.5-14B: —, Qwen3.5-Flash: —

Agentic & Tool Use benchmarks
BenchmarkQwen1.5-14BQwen3.5-Flash
Vending-Bench 2—462.69

Reasoning Qwen3.5-Flash leads

Qwen1.5-14B: 21.4 (#223), Qwen3.5-Flash: 33.7 (#72)

Reasoning benchmarks
BenchmarkQwen1.5-14BQwen3.5-Flash
LMArena Hard Prompts11131403
Chess Puzzles—21%
Mystery Game Puzzles—20%
DTBench—82.9%
LMCA—29.1%
Epoch Capabilities Index—143.98

Math Qwen3.5-Flash leads

Qwen1.5-14B: 32.4 (#215), Qwen3.5-Flash: 37.4 (#158)

Math benchmarks
BenchmarkQwen1.5-14BQwen3.5-Flash
LMArena Math11251407
FrontierMath (Tiers 1-3)—18.2%
OTIS Mock AIME 2024-2025—84.4%
FrontierMath (Feb 2025 set)—6.2%
FrontierMath Tier 4 (v1)—0%

Knowledge Qwen3.5-Flash leads

Qwen1.5-14B: 29.8 (#232), Qwen3.5-Flash: 43.2 (#93)

Knowledge benchmarks
BenchmarkQwen1.5-14BQwen3.5-Flash
LMArena Expert10941407
GPQA Diamond—82.3%
SimpleQA Verified—20.3%
Vectara Hallucination Rate—10.5%
MMLU68.6%—

Multilingual Qwen3.5-Flash leads

Qwen1.5-14B: 30.7 (#262), Qwen3.5-Flash: 50.5 (#121)

Multilingual benchmarks
BenchmarkQwen1.5-14BQwen3.5-Flash
LMArena Non-English10951385
LMArena Chinese11471446
LMArena French11161412
LMArena German10431390
LMArena Japanese10191368
LMArena Russian10461379
LMArena Spanish10851400
LMArena Korean—1344

Instruction Following Qwen3.5-Flash leads

Qwen1.5-14B: 56.8 (#271), Qwen3.5-Flash: 72.6 (#139)

Instruction Following benchmarks
BenchmarkQwen1.5-14BQwen3.5-Flash
LMArena Instruction Following11021374

Long Context Qwen3.5-Flash leads

Qwen1.5-14B: 33.7 (#257), Qwen3.5-Flash: 42.4 (#124)

Long Context benchmarks
BenchmarkQwen1.5-14BQwen3.5-Flash
LMArena Longer Query11131392

Writing & Preference Qwen3.5-Flash leads

Qwen1.5-14B: 33.6 (#276), Qwen3.5-Flash: 57.9 (#122)

Writing & Preference benchmarks
BenchmarkQwen1.5-14BQwen3.5-Flash
LMArena Text11281397
LMArena Creative Writing10911343
LMArena Multi-Turn11101393

Frequently asked questions

Is Qwen1.5-14B better than Qwen3.5-Flash?

Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 32.7 on the Noometry Index.

Is Qwen1.5-14B or Qwen3.5-Flash better for coding?

Qwen3.5-Flash scores higher on coding benchmarks: 34.2 versus 33.1 in the Noometry coding category.

How many benchmarks do Qwen1.5-14B and Qwen3.5-Flash share?

16 benchmarks have published results for both models. Qwen1.5-14B has 17 scored results on Noometry and Qwen3.5-Flash has 32.

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