Model comparison

Llama 4 Scout vs Qwen1.5-110B

Qwen1.5-110B is the stronger model overall, scoring 34.2 to 27.7 on the Noometry Index.

Last verified . 19 shared benchmarks.

Llama 4 Scout Meta

27.7

Rank #330 Confirmed

Qwen1.5-110B Alibaba (Qwen)

34.2

Rank #234 Confirmed

Summary

  • They share 19 benchmarks with published results for both. Llama 4 Scout scores higher in 3 categories and Qwen1.5-110B in 5 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in math, where Qwen1.5-110B leads 33.7 to 19.6.

Side by side

Llama 4 Scout and Qwen1.5-110B specifications
Llama 4 ScoutQwen1.5-110B
ProviderMetaAlibaba (Qwen)
Noometry Index27.734.2
Released2025-04-052024-04-25
WeightsOpenOpen
Context window128K—
Max output4K—
Input $ / M tokens$0.10—
Output $ / M tokens$0.30—
Results tracked4320

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Category by category

Coding Qwen1.5-110B leads

Llama 4 Scout: 20.2 (#339), Qwen1.5-110B: 33.0 (#264)

Coding benchmarks
BenchmarkLlama 4 ScoutQwen1.5-110B
LMArena Coding12861184
BigCodeBench Complete43.1%44.4%
SWE-bench Verified (bash only)9.1%—
SciCode17%—
BigCodeBench Instruct—35%

Agentic & Tool Use Not comparable

Llama 4 Scout: 24.6 (#119), Qwen1.5-110B: —

Agentic & Tool Use benchmarks
BenchmarkLlama 4 ScoutQwen1.5-110B
Berkeley Function Calling Leaderboard28.1%—

Reasoning Qwen1.5-110B leads

Llama 4 Scout: 9.1 (#345), Qwen1.5-110B: 22.7 (#189)

Reasoning benchmarks
BenchmarkLlama 4 ScoutQwen1.5-110B
LMArena Hard Prompts12661168
ForecastBench57.557.7
ARC-AGI-20%—
Kagi LLM Benchmark36.9%—
ARC-AGI-10.5%—
CritPt0%—
DTBench57.9%—
LMCA12%—
Epoch Capabilities Index129.64—

Math Qwen1.5-110B leads

Llama 4 Scout: 19.6 (#286), Qwen1.5-110B: 33.7 (#201)

Math benchmarks
BenchmarkLlama 4 ScoutQwen1.5-110B
LMArena Math12871185
OTIS Mock AIME 2024-20257.8%—
Omni-MATH37.3%—
MATH Level 562.3%—
FrontierMath (Feb 2025 set)0%—

Knowledge Too close to call

Llama 4 Scout: 31.9 (#217), Qwen1.5-110B: 31.2 (#219)

Knowledge benchmarks
BenchmarkLlama 4 ScoutQwen1.5-110B
LMArena Expert12351144
GPQA Diamond51.8%—
MMLU-Pro74.2%—
Vectara Hallucination Rate7.7%—
GPQA (HELM)50.7%—

Multimodal Not comparable

Llama 4 Scout: 32.2 (#102), Qwen1.5-110B: —

Multimodal benchmarks
BenchmarkLlama 4 ScoutQwen1.5-110B
LMArena Vision1118—
SpatialViz-Bench34.2%—

Multilingual Llama 4 Scout leads

Llama 4 Scout: 41.0 (#212), Qwen1.5-110B: 33.6 (#250)

Multilingual benchmarks
BenchmarkLlama 4 ScoutQwen1.5-110B
LMArena Non-English12521142
LMArena Chinese12551206
LMArena French12821151
LMArena German12721123
LMArena Japanese12061074
LMArena Korean12071044
LMArena Russian12631118
LMArena Spanish12781142

Instruction Following Llama 4 Scout leads

Llama 4 Scout: 65.8 (#217), Qwen1.5-110B: 60.3 (#252)

Instruction Following benchmarks
BenchmarkLlama 4 ScoutQwen1.5-110B
LMArena Instruction Following12481158
IFEval81.8%—

Long Context Qwen1.5-110B leads

Llama 4 Scout: 27.5 (#294), Qwen1.5-110B: 35.1 (#242)

Long Context benchmarks
BenchmarkLlama 4 ScoutQwen1.5-110B
LMArena Longer Query12651157
Fiction.LiveBench36%—

Writing & Preference Too close to call

Llama 4 Scout: 37.0 (#261), Qwen1.5-110B: 38.0 (#255)

Writing & Preference benchmarks
BenchmarkLlama 4 ScoutQwen1.5-110B
LMArena Text12791175
LMArena Creative Writing12491148
LMArena Multi-Turn12801160
EQ-Bench Creative Writing783—
WildBench78%—

Frequently asked questions

Is Llama 4 Scout better than Qwen1.5-110B?

Qwen1.5-110B is the stronger model overall, scoring 34.2 to 27.7 on the Noometry Index.

Is Llama 4 Scout or Qwen1.5-110B better for coding?

Qwen1.5-110B scores higher on coding benchmarks: 33.0 versus 20.2 in the Noometry coding category.

How many benchmarks do Llama 4 Scout and Qwen1.5-110B share?

19 benchmarks have published results for both models. Llama 4 Scout has 43 scored results on Noometry and Qwen1.5-110B has 20.

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