Llama 4 Scout
MetaLlamaOpen WeightLlama 4 Community License Agreement
Descripción
Llama 4 Scout is a natively multimodal model capable of processing both text and images. It features a 17 billion activated parameter (109B total) mixture-of-experts (MoE) architecture with 16 experts, supporting a wide range of multimodal tasks such as conversational interaction, image analysis, and code generation. The model includes a 10 million token context window.
Fecha de lanzamiento
2025-04-05
Parámetros
109.0B
Longitud del contexto
1.3M
Modalidades
image, text
Radar de capacidades
29
general
17
coding
33
reasoning
33
science
28
agents
90
multimodal
Rankings
| Dominio | #Posición | Puntuación | Fuente |
|---|---|---|---|
| Ranking de codificación | 443 | 18.0 | AA |
| Ranking general | 383 | 33.0 | AA |
| Ciencia | 432 | 30.0 | AA |
Puntuaciones de benchmarks (LLM Stats)
(LLM Stats (zeroeval))Biology
GPQANYU + Cohere + Anthropic (2023)
57.2%Aut.
Code
LiveCodeBench
32.8%Aut.
Finance
MMLU
79.6%Aut.
MMLU-Pro
74.3%Aut.
General
MMMU
69.4%Aut.
MBPP
0.68 / 100Aut.
Image To Text
DocVQADocVQA (2020)
94.4%Aut.
Language
TydiQA
31.5%Aut.
Math
MGSM
90.6%Aut.
MathVista
70.7%Aut.
MATH
50.3%Aut.
Multimodal
ChartQAMasry et al. (2022)
88.8%Aut.
Índices de evaluación AA
(Artificial Analysis)Math Index(Artificial Analysis)14.0
Intelligence Index(Artificial Analysis)10.3
Coding Index(Artificial Analysis)8.2
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))0.8
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))0.8
Gpqa(NYU + Cohere + Anthropic (2023))0.6
Ifbench(Google Research (2023))0.4
Lcr(Artificial Analysis)0.3
Livecodebench(UC Berkeley + MIT + Cornell (2024))0.3
Aime(MAA (Mathematical Association of America))0.3
Scicode(UIUC + Argonne National Lab (2024))0.2
Tau2(Sierra + U Toronto + Vector Institute (2025))0.2
Aime 25(MAA (Mathematical Association of America))0.1
Hle(Center for AI Safety + Scale AI (2025))0.0
Terminalbench V2 10.0
Tau Banking0.0
Terminalbench Hard(Stanford × Laude Institute (2026))0.0
Puntuaciones por categoría LLM Stats
(LLM Stats (zeroeval))Image To Text90
Legal80
Multimodal80
Language80
Finance80
Vision80
Math70
Reasoning70
General70
Healthcare70
Physics60
Biology60
Chemistry60
Code30
Precios
Precio de entrada$0.18 / 1M tokens
Precio de salida$0.66 / 1M tokens
Precio mixto (3:1)$0.3 / 1M tokens
Velocidad
Tokens/seg129.9
Retraso del primer token0.61s
Tiempo hasta la respuesta0.61s
Ranking de Precios por Proveedor
Ranking de Precios por Proveedor
5 proveedores
Más barato: HeliconeMás caro: Meta
ProveedorEntradaSalida
1HeliconeMás barato
$0.08
$0.3
2NanoGPT
$0.085
$0.46
3OpenRouter
$0.1
$0.3
4Kilo Gateway
$0.1
$0.3
5MetaPRINCIPAL
$0.18
$0.66
Comparar precios entre diferentes proveedores de API para este modelo.