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Nova Pro

AmazonAmazonProprietary

Descripción

Amazon Nova Pro is a highly-capable multimodal model with state-of-the-art performance across text, image, and video understanding. It excels at core capabilities like language understanding, mathematical reasoning, and multimodal tasks while offering industry-leading speed and cost efficiency.

Fecha de lanzamiento
2024-12-03
Parámetros
—
Longitud del contexto
300K
Modalidades
image, pdf, text, video

Radar de capacidades

25
general
23
coding
23
reasoning
36
science
70
agents
90
multimodal

Rankings

Dominio#PosiciónPuntuaciónFuente
Ranking de codificación518
19.0
AA
Ranking general499
28.0
AA
Ranking multimodal128
35.0
LS
Ciencia525
25.0
AA

Puntuaciones de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Chat

IFEvalGoogle Research (2023)92.1%Aut.

Finance

FinQA77.2%Aut.

General

MMLU85.9%Aut.
BFCL68.4%Aut.

Language

Translation en→Set1 COMET2289.1%Aut.
Translation Set1→en COMET2289.0%Aut.
Translation Set1→en spBleu44.4%Aut.
Translation en→Set1 spBleu43.4%Aut.

Math

GSM8k94.8%Aut.
MATH76.6%Aut.

Multimodal

GroundUI-1K81.4%Aut.
VATEX77.8%Aut.
MM-Mind2Web63.7%Aut.
MMMU61.7%Aut.

Reasoning

ARC-C94.8%Aut.
ChartQAMasry et al. (2022)89.2%Aut.
HumanEvalOpenAI (2021)89.0%Aut.
BBH86.9%Aut.
DROP85.4%Aut.
CRAG50.3%Aut.
GPQANYU + Cohere + Anthropic (2023)46.9%Aut.

Summarization

SQuALITY19.8%Aut.

Vision

DocVQADocVQA (2020)93.5%Aut.
TextVQA81.5%Aut.
VisualWebBench79.7%Aut.
EgoSchema72.1%Aut.
LVBench41.6%Aut.

Índices de evaluación AA

(Artificial Analysis)
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))
78.6
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
69.1
Gpqa(NYU + Cohere + Anthropic (2023))
49.9
Ifbench(Google Research (2023))
38.1
Livecodebench(UC Berkeley + MIT + Cornell (2024))
23.3
Lcr(Artificial Analysis)
21.0
Tau2(Sierra + U Toronto + Vector Institute (2025))
14.0
Aime(MAA (Mathematical Association of America))
10.7
Aime 25(MAA (Mathematical Association of America))
7.0
Intelligence Index(Artificial Analysis)
7.0
Math Index(Artificial Analysis)
7.0
Terminalbench Hard(Stanford × Laude Institute (2026))
6.1
Hle(Center for AI Safety + Scale AI (2025))
3.2

Puntuaciones por categoría LLM Stats

(LLM Stats (zeroeval))
Chat
90
Image To Text
90
Instruction Following
90
Legal
90
Structured Output
90
Code
90
Math
80
Reasoning
80
Language
70
Multimodal
70
Finance
70
General
70
Healthcare
70
Tool Calling
70
Vision
70
Frontend Development
60
Agents
60
Economics
60
Physics
50
Search
50
Biology
50
Chemistry
50
Long Context
40
Summarization
20

Precios

Precio de entrada$0.8 / 1M tokens
Precio de salida$3.2 / 1M tokens
Precio mixto (3:1)$1.4 / 1M tokens
Precio de lectura caché$0.2 / 1M tokens
Precio de escritura caché$0.8 / 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: AmazonMás caro: Amazon Bedrock
ProveedorEntradaSalida
1AmazonPRINCIPAL
$0.8
$3.2
2Amazon Bedrock
$0.8
$3.2

Comparar precios entre diferentes proveedores de API para este modelo.

Fuentes externas