Model comparison

Llama 4 Scout vs Qwen1.5-7B

Qwen1.5-7B is the stronger model overall, scoring 30.8 to 27.4 on the Noometry Index.

Last verified . 12 shared benchmarks.

Llama 4 Scout Meta

27.4

Rank #323 Confirmed

Qwen1.5-7B Alibaba (Qwen)

30.8

Rank #270 Confirmed

Summary

  • They share 12 benchmarks with published results for both. Llama 4 Scout scores higher in 4 categories and Qwen1.5-7B in 4 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in multilingual, where Llama 4 Scout leads 41.3 to 28.6.

Side by side

Llama 4 Scout and Qwen1.5-7B specifications
Llama 4 ScoutQwen1.5-7B
ProviderMetaAlibaba (Qwen)
Noometry Index27.430.8
Released2025-04-052024-02-04
WeightsOpenOpen
Context window128K—
Max output4K—
Input $ / M tokens$0.10—
Output $ / M tokens$0.30—
Results tracked4313

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Category by category

Coding Qwen1.5-7B leads

Llama 4 Scout: 19.9 (#334), Qwen1.5-7B: 31.6 (#271)

Coding benchmarks
BenchmarkLlama 4 ScoutQwen1.5-7B
LMArena Coding12861107
SWE-bench Verified (bash only)9.1%—
SciCode17%—
BigCodeBench Complete43.1%—

Agentic & Tool Use Not comparable

Llama 4 Scout: 24.4 (#109), Qwen1.5-7B: —

Agentic & Tool Use benchmarks
BenchmarkLlama 4 ScoutQwen1.5-7B
Berkeley Function Calling Leaderboard28.1%—

Reasoning Qwen1.5-7B leads

Llama 4 Scout: 9.2 (#339), Qwen1.5-7B: 19.5 (#237)

Reasoning benchmarks
BenchmarkLlama 4 ScoutQwen1.5-7B
LMArena Hard Prompts12661066
ARC-AGI-20%—
Kagi LLM Benchmark36.9%—
ARC-AGI-10.5%—
CritPt0%—
DTBench57.9%—
LMCA12%—
Epoch Capabilities Index129.64—
ForecastBench57.5—

Math Qwen1.5-7B leads

Llama 4 Scout: 18.4 (#280), Qwen1.5-7B: 29.0 (#222)

Math benchmarks
BenchmarkLlama 4 ScoutQwen1.5-7B
LMArena Math12861080
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: 31.8 (#208), Qwen1.5-7B: 28.2 (#239)

Knowledge benchmarks
BenchmarkLlama 4 ScoutQwen1.5-7B
LMArena Expert12361055
GPQA Diamond51.8%—
MMLU-Pro74.2%—
Vectara Hallucination Rate7.7%—
GPQA (HELM)50.7%—
MMLU—62.6%

Multimodal Not comparable

Llama 4 Scout: 31.6 (#98), Qwen1.5-7B: —

Multimodal benchmarks
BenchmarkLlama 4 ScoutQwen1.5-7B
LMArena Vision1118—
SpatialViz-Bench34.2%—

Multilingual Llama 4 Scout leads

Llama 4 Scout: 41.3 (#207), Qwen1.5-7B: 28.6 (#266)

Multilingual benchmarks
BenchmarkLlama 4 ScoutQwen1.5-7B
LMArena Non-English12531058
LMArena Chinese12561140
LMArena Russian12631006
LMArena French1283—
LMArena German1274—
LMArena Japanese1209—
LMArena Korean1207—
LMArena Spanish1277—

Instruction Following Llama 4 Scout leads

Llama 4 Scout: 66.0 (#212), Qwen1.5-7B: 54.4 (#276)

Instruction Following benchmarks
BenchmarkLlama 4 ScoutQwen1.5-7B
LMArena Instruction Following12481058
IFEval81.8%—

Long Context Qwen1.5-7B leads

Llama 4 Scout: 27.5 (#289), Qwen1.5-7B: 33.1 (#261)

Long Context benchmarks
BenchmarkLlama 4 ScoutQwen1.5-7B
LMArena Longer Query12651090
Fiction.LiveBench36%—

Writing & Preference Llama 4 Scout leads

Llama 4 Scout: 37.1 (#256), Qwen1.5-7B: 29.8 (#288)

Writing & Preference benchmarks
BenchmarkLlama 4 ScoutQwen1.5-7B
LMArena Text12791084
LMArena Creative Writing12491035
LMArena Multi-Turn12811061
EQ-Bench Creative Writing783—
WildBench78%—

Frequently asked questions

Is Llama 4 Scout better than Qwen1.5-7B?

Qwen1.5-7B is the stronger model overall, scoring 30.8 to 27.4 on the Noometry Index.

Is Llama 4 Scout or Qwen1.5-7B better for coding?

Qwen1.5-7B scores higher on coding benchmarks: 31.6 versus 19.9 in the Noometry coding category.

How many benchmarks do Llama 4 Scout and Qwen1.5-7B share?

12 benchmarks have published results for both models. Llama 4 Scout has 43 scored results on Noometry and Qwen1.5-7B has 13.

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