Noometry

Model comparison

Llama 4 Scout vs Qwen1.5-32B

Qwen1.5-32B is the stronger model overall, scoring 30.5 to 27.7 on the Noometry Index.

Last verified . 19 shared benchmarks.

Llama 4 Scout Meta

27.7

Rank #330 Confirmed

Qwen1.5-32B Alibaba (Qwen)

30.5

Rank #293 Confirmed

Summary

  • They share 19 benchmarks with published results for both. Llama 4 Scout scores higher in 4 categories and Qwen1.5-32B in 4 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Llama 4 Scout leads 31.9 to 13.5.
  • The biggest single-benchmark swing is GPQA Diamond: 51.8% for Llama 4 Scout and 30.7% for Qwen1.5-32B.

Side by side

Llama 4 ScoutQwen1.5-32B
ProviderMetaAlibaba (Qwen)
Noometry Index27.730.5
Released2025-04-052024-02-04
WeightsOpenOpen
Context window128K—
Max output4K—
Input $ / M tokens$0.10—
Output $ / M tokens$0.30—
Results tracked4321

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Category by category

Coding Qwen1.5-32B leads

Llama 4 Scout: 20.2 (#339), Qwen1.5-32B: 31.7 (#282)

BenchmarkLlama 4 ScoutQwen1.5-32B
LMArena Coding12861155
BigCodeBench Complete43.1%42%
SWE-bench Verified (bash only)9.1%—
SciCode17%—
BigCodeBench Instruct—32.3%

Agentic & Tool Use Not comparable

Llama 4 Scout: 24.6 (#119), Qwen1.5-32B: —

BenchmarkLlama 4 ScoutQwen1.5-32B
Berkeley Function Calling Leaderboard28.1%—

Reasoning Qwen1.5-32B leads

Llama 4 Scout: 9.1 (#345), Qwen1.5-32B: 21.8 (#212)

BenchmarkLlama 4 ScoutQwen1.5-32B
LMArena Hard Prompts12661130
ARC-AGI-20%—
Kagi LLM Benchmark36.9%—
ARC-AGI-10.5%—
CritPt0%—
DTBench57.9%—
LMCA12%—
Epoch Capabilities Index129.64—
ForecastBench57.5—

Math Qwen1.5-32B leads

Llama 4 Scout: 19.6 (#286), Qwen1.5-32B: 33.0 (#207)

BenchmarkLlama 4 ScoutQwen1.5-32B
LMArena Math12871155
OTIS Mock AIME 2024-20257.8%—
Omni-MATH37.3%—
MATH Level 562.3%—
FrontierMath (Feb 2025 set)0%—

Knowledge Llama 4 Scout leads

Llama 4 Scout: 31.9 (#217), Qwen1.5-32B: 13.5 (#296)

BenchmarkLlama 4 ScoutQwen1.5-32B
GPQA Diamond51.8%30.7%
LMArena Expert12351126
MMLU-Pro74.2%—
Vectara Hallucination Rate7.7%—
GPQA (HELM)50.7%—
MMLU—74.4%

Multimodal Not comparable

Llama 4 Scout: 32.2 (#102), Qwen1.5-32B: —

BenchmarkLlama 4 ScoutQwen1.5-32B
LMArena Vision1118—
SpatialViz-Bench34.2%—

Multilingual Llama 4 Scout leads

Llama 4 Scout: 41.0 (#212), Qwen1.5-32B: 31.4 (#259)

BenchmarkLlama 4 ScoutQwen1.5-32B
LMArena Non-English12521106
LMArena Chinese12551177
LMArena French12821101
LMArena German12721058
LMArena Japanese12061027
LMArena Korean12071008
LMArena Russian12631073
LMArena Spanish12781089

Instruction Following Llama 4 Scout leads

Llama 4 Scout: 65.8 (#217), Qwen1.5-32B: 57.7 (#265)

BenchmarkLlama 4 ScoutQwen1.5-32B
LMArena Instruction Following12481116
IFEval81.8%—

Long Context Qwen1.5-32B leads

Llama 4 Scout: 27.5 (#294), Qwen1.5-32B: 34.7 (#246)

BenchmarkLlama 4 ScoutQwen1.5-32B
LMArena Longer Query12651146
Fiction.LiveBench36%—

Writing & Preference Llama 4 Scout leads

Llama 4 Scout: 37.0 (#261), Qwen1.5-32B: 34.2 (#271)

BenchmarkLlama 4 ScoutQwen1.5-32B
LMArena Text12791137
LMArena Creative Writing12491083
LMArena Multi-Turn12801140
EQ-Bench Creative Writing783—
WildBench78%—

Frequently asked questions

Is Llama 4 Scout better than Qwen1.5-32B?

Qwen1.5-32B is the stronger model overall, scoring 30.5 to 27.7 on the Noometry Index.

Is Llama 4 Scout or Qwen1.5-32B better for coding?

Qwen1.5-32B scores higher on coding benchmarks: 31.7 versus 20.2 in the Noometry coding category.

How many benchmarks do Llama 4 Scout and Qwen1.5-32B share?

19 benchmarks have published results for both models. Llama 4 Scout has 43 scored results on Noometry and Qwen1.5-32B has 21.

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