Model comparison

Llama 2-7B vs Llama 4 Scout

Llama 2-7B is the stronger model overall, scoring 29.1 to 27.7 on the Noometry Index.

Last verified . 16 shared benchmarks.

Llama 2-7B Meta

29.1

Rank #317 Confirmed

Llama 4 Scout Meta

27.7

Rank #330 Confirmed

Summary

  • They share 16 benchmarks with published results for both. Llama 2-7B scores higher in 4 categories and Llama 4 Scout in 4 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in multilingual, where Llama 4 Scout leads 41.0 to 23.8.

Side by side

Llama 2-7B and Llama 4 Scout specifications
Llama 2-7BLlama 4 Scout
ProviderMetaMeta
Noometry Index29.127.7
Released2023-07-182025-04-05
WeightsOpenOpen
Context window—128K
Max output—4K
Input $ / M tokens—$0.10
Output $ / M tokens—$0.30
Results tracked2943

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Category by category

Coding Llama 2-7B leads

Llama 2-7B: 29.2 (#307), Llama 4 Scout: 20.2 (#339)

Coding benchmarks
BenchmarkLlama 2-7BLlama 4 Scout
LMArena Coding10021286
SWE-bench Verified (bash only)—9.1%
SciCode—17%
BigCodeBench Complete—43.1%

Agentic & Tool Use Not comparable

Llama 2-7B: —, Llama 4 Scout: 24.6 (#119)

Agentic & Tool Use benchmarks
BenchmarkLlama 2-7BLlama 4 Scout
Berkeley Function Calling Leaderboard—28.1%

Reasoning Llama 2-7B leads

Llama 2-7B: 15.7 (#312), Llama 4 Scout: 9.1 (#345)

Reasoning benchmarks
BenchmarkLlama 2-7BLlama 4 Scout
LMArena Hard Prompts10091266
Epoch Capabilities Index99.06129.64
ARC-AGI-2—0%
Kagi LLM Benchmark—36.9%
ARC-AGI-1—0.5%
CritPt—0%
Chess Puzzles0%—
DTBench—57.9%
LMCA—12%
BIG-Bench Hard39.2%—
ForecastBench—57.5
HellaSwag77.2%—
LAMBADA73.3%—
PIQA78.8%—
WinoGrande69.2%—

Math Llama 2-7B leads

Llama 2-7B: 30.7 (#233), Llama 4 Scout: 19.6 (#286)

Math benchmarks
BenchmarkLlama 2-7BLlama 4 Scout
LMArena Math10421287
OTIS Mock AIME 2024-2025—7.8%
Omni-MATH—37.3%
MATH Level 5—62.3%
FrontierMath (Feb 2025 set)—0%
GSM8K16.7%—

Knowledge Llama 4 Scout leads

Llama 2-7B: 28.2 (#248), Llama 4 Scout: 31.9 (#217)

Knowledge benchmarks
BenchmarkLlama 2-7BLlama 4 Scout
LMArena Expert10361235
GPQA Diamond—51.8%
MMLU-Pro—74.2%
Vectara Hallucination Rate—7.7%
GPQA (HELM)—50.7%
ARC (AI2) Challenge45.9%—
BoolQ77.9%—
MMLU45.8%—
OpenBookQA58.6%—
TriviaQA73.7%—

Multimodal Not comparable

Llama 2-7B: —, Llama 4 Scout: 32.2 (#102)

Multimodal benchmarks
BenchmarkLlama 2-7BLlama 4 Scout
LMArena Vision—1118
ScienceQA43.1%—
SpatialViz-Bench—34.2%

Multilingual Llama 4 Scout leads

Llama 2-7B: 23.8 (#293), Llama 4 Scout: 41.0 (#212)

Multilingual benchmarks
BenchmarkLlama 2-7BLlama 4 Scout
LMArena Non-English9731252
LMArena Chinese9731255
LMArena French9701282
LMArena German9781272
LMArena Russian9951263
LMArena Spanish10071278
LMArena Japanese—1206
LMArena Korean—1207

Instruction Following Llama 4 Scout leads

Llama 2-7B: 50.8 (#298), Llama 4 Scout: 65.8 (#217)

Instruction Following benchmarks
BenchmarkLlama 2-7BLlama 4 Scout
LMArena Instruction Following10061248
IFEval—81.8%

Long Context Llama 2-7B leads

Llama 2-7B: 30.4 (#287), Llama 4 Scout: 27.5 (#294)

Long Context benchmarks
BenchmarkLlama 2-7BLlama 4 Scout
LMArena Longer Query9991265
Fiction.LiveBench—36%

Writing & Preference Llama 4 Scout leads

Llama 2-7B: 28.0 (#298), Llama 4 Scout: 37.0 (#261)

Writing & Preference benchmarks
BenchmarkLlama 2-7BLlama 4 Scout
LMArena Text10531279
LMArena Creative Writing10331249
LMArena Multi-Turn10291280
EQ-Bench Creative Writing—783
WildBench—78%

Frequently asked questions

Is Llama 2-7B better than Llama 4 Scout?

Llama 2-7B is the stronger model overall, scoring 29.1 to 27.7 on the Noometry Index.

Is Llama 2-7B or Llama 4 Scout better for coding?

Llama 2-7B scores higher on coding benchmarks: 29.2 versus 20.2 in the Noometry coding category.

How many benchmarks do Llama 2-7B and Llama 4 Scout share?

16 benchmarks have published results for both models. Llama 2-7B has 29 scored results on Noometry and Llama 4 Scout has 43.

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