Llama 3.1 Instruct 8B
MetaLlamaOpen WeightLlama 3.1 Community License
Descripción
Llama 3.1 8B Instruct is a multilingual large language model optimized for dialogue use cases. It features a 128K context length, state-of-the-art tool use, and strong reasoning capabilities.
Fecha de lanzamiento
2024-07-23
Parámetros
8.0B
Longitud del contexto
131K
Modalidades
text
Radar de capacidades
19
general
8
coding
14
reasoning
20
science
50
agents
0
multimodal
Rankings
| Dominio | #Posición | Puntuación | Fuente |
|---|---|---|---|
| Ranking de codificación | 593 | 9.0 | AA |
| Ranking general | 567 | 21.0 | AA |
| Ciencia | 634 | 13.0 | AA |
Puntuaciones de benchmarks (LLM Stats)
(LLM Stats (zeroeval))Chat
IFEvalGoogle Research (2023)
80.4%Aut.
General
BFCL
76.1%Aut.
MMLU
69.4%Aut.
Multipl-E MBPP
52.4%Aut.
Nexus
38.5%Aut.
Language
MMLU (CoT)
73.0%Aut.
Multipl-E HumanEval
50.8%Aut.
MMLU-Pro
48.3%Aut.
Math
GSM-8K (CoT)
84.5%Aut.
Multilingual MGSM (CoT)
68.9%Aut.
MATH (CoT)
51.9%Aut.
Reasoning
ARC-C
83.4%Aut.
API-Bank
82.6%Aut.
MBPP EvalPlus (base)
72.8%Aut.
HumanEvalOpenAI (2021)
72.6%Aut.
DROP
59.5%Aut.
GPQANYU + Cohere + Anthropic (2023)
30.4%Aut.
Gorilla Benchmark API Bench
8.2%Aut.
Índices de evaluación AA
(Artificial Analysis)Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))51.9
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))47.6
Ifbench(Google Research (2023))28.6
Gpqa(NYU + Cohere + Anthropic (2023))25.9
Lcr(Artificial Analysis)18.0
Tau2(Sierra + U Toronto + Vector Institute (2025))16.4
Livecodebench(UC Berkeley + MIT + Cornell (2024))11.6
Aime(MAA (Mathematical Association of America))7.7
Intelligence Index(Artificial Analysis)6.9
Coding Index(Artificial Analysis)5.4
Hle(Center for AI Safety + Scale AI (2025))5.3
Aime 25(MAA (Mathematical Association of America))4.3
Math Index(Artificial Analysis)4.3
Terminalbench V2 11.5
Terminalbench Hard(Stanford × Laude Institute (2026))0.8
Puntuaciones por categoría LLM Stats
(LLM Stats (zeroeval))Chat80
Instruction Following80
Structured Output80
Language60
Legal60
Math60
Reasoning60
Finance60
General60
Healthcare60
Tool Calling50
Code40
Physics30
Biology30
Chemistry30
Precios
Precio de entrada$0.02 / 1M tokens
Precio de salida$0.05 / 1M tokens
Precio mixto (3:1)$0.028 / 1M tokens
Precio de lectura caché$0.025 / 1M tokens
Velocidad
Tokens/seg0.0
Retraso del primer token0.00s
Tiempo hasta la respuesta0.00s
Ranking de Precios por Proveedor
Ranking de Precios por Proveedor
2 proveedores
Más barato: DeepInfraMás caro: Meta
ProveedorEntradaSalida
1DeepInfraMás barato
$0
$0
2MetaPRINCIPAL
$0.02
$0.05
Comparar precios entre diferentes proveedores de API para este modelo.