Phi-4 Mini Instruct
MicrosoftPhiOpen WeightMIT · Uso Comercial
Descripción
Phi 4 Mini Instruct is a lightweight (3.8B parameters) open model built upon synthetic data and filtered web data, focusing on high-quality reasoning. It supports a 128K token context length and is enhanced for instruction adherence and safety via supervised fine-tuning and direct preference optimization.
Fecha de lanzamiento
2024-02-26
Parámetros
3.8B
Longitud del contexto
—
Modalidades
—
Radar de capacidades
18
general
8
coding
18
reasoning
20
science
15
agents
0
multimodal
Rankings
| Dominio | #Posición | Puntuación | Fuente |
|---|---|---|---|
| Ranking de codificación | 515 | 9.0 | AA |
| Ranking general | 526 | 17.0 | AA |
| Ciencia | 518 | 17.0 | AA |
Puntuaciones de benchmarks (LLM Stats)
(LLM Stats (zeroeval))Biology
GPQANYU + Cohere + Anthropic (2023)
52.0%Aut.
Creativity
Social IQa
72.5%Aut.
Arena Hard
32.8%Aut.
Finance
MMLU
67.3%Aut.
TruthfulQA
66.4%Aut.
MMLU-Pro
52.8%Aut.
General
ARC-C
83.7%Aut.
OpenBookQA
79.2%Aut.
PIQA
77.6%Aut.
Multilingual MMLU
49.3%Aut.
Language
BoolQ
81.2%Aut.
BIG-Bench Hard
70.4%Aut.
Winogrande
67.0%Aut.
Math
MATH-500
94.6%Aut.
GSM8k
88.6%Aut.
MATH
64.0%Aut.
MGSM
63.9%Aut.
AIMEMAA
57.5%Aut.
Reasoning
HellaSwagAI2 (2019)
69.1%Aut.
Índices de evaluación AA
(Artificial Analysis)Math Index(Artificial Analysis)6.7
Intelligence Index(Artificial Analysis)5.7
Coding Index(Artificial Analysis)3.8
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))0.7
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))0.5
Gpqa(NYU + Cohere + Anthropic (2023))0.3
Ifbench(Google Research (2023))0.2
Lcr(Artificial Analysis)0.2
Livecodebench(UC Berkeley + MIT + Cornell (2024))0.1
Scicode(UIUC + Argonne National Lab (2024))0.1
Tau2(Sierra + U Toronto + Vector Institute (2025))0.1
Aime 25(MAA (Mathematical Association of America))0.1
Hle(Center for AI Safety + Scale AI (2025))0.0
Aime(MAA (Mathematical Association of America))0.0
Terminalbench V2 10.0
Terminalbench Hard(Stanford × Laude Institute (2026))0.0
Puntuaciones por categoría LLM Stats
(LLM Stats (zeroeval))Math70
Psychology70
Reasoning70
General70
Legal60
Language60
Finance60
Healthcare60
Physics50
Creativity50
Biology30
Chemistry30
Writing30
Precios
Precio de entradaGratis
Precio de salidaGratis
Precio mixto (3:1)Gratis
Velocidad
Tokens/seg45.1
Retraso del primer token0.34s
Tiempo hasta la respuesta0.34s
Ranking de Precios por Proveedor
Ranking de Precios por Proveedor
2 proveedores
Más barato: Azure Cognitive ServicesMás caro: Azure
ProveedorEntradaSalida
1Azure Cognitive ServicesMás barato
$0.075
$0.3
2Azure
$0.075
$0.3
Comparar precios entre diferentes proveedores de API para este modelo.