Nova Pro

AmazonAmazonProprietary

描述

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.

發布日期

2024-12-03

參數規模

—

上下文長度

300K

支援模態

image, text, video

能力雷達圖

general

coding

reasoning

science

agents

multimodal

排行榜排名

領域	#排名	分數	來源
程式碼能力榜	415	20.0	AA
通用能力榜	434	29.0	AA
科學能力	437	29.0	AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Agents

MM-Mind2Web

63.7%自報

Biology

GPQANYU + Cohere + Anthropic (2023)

46.9%自報

Code

HumanEvalOpenAI (2021)

89.0%自報

Economics

FinQA

77.2%自報

CRAG

50.3%自報

Finance

MMLU

85.9%自報

Frontend Development

VisualWebBench

79.7%自報

General

ARC-C

94.8%自報

IFEvalGoogle Research (2023)

92.1%自報

BFCL

68.4%自報

MMMU

61.7%自報

Grounding

GroundUI-1K

81.4%自報

Image To Text

DocVQADocVQA (2020)

93.5%自報

TextVQA

81.5%自報

Language

Translation en→Set1 COMET22

89.1%自報

Translation Set1→en COMET22

89.0%自報

BBH

86.9%自報

VATEX

77.8%自報

Translation Set1→en spBleu

44.4%自報

Translation en→Set1 spBleu

43.4%自報

SQuALITY

19.8%自報

Long Context

EgoSchema

72.1%自報

LVBench

41.6%自報

Math

GSM8k

94.8%自報

DROP

85.4%自報

MATH

76.6%自報

Multimodal

ChartQAMasry et al. (2022)

89.2%自報

AA 評測指數

(Artificial Analysis)

Intelligence Index(Artificial Analysis)

7.5

Math Index(Artificial Analysis)

7.0

Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))

0.8

Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))

0.7

Gpqa(NYU + Cohere + Anthropic (2023))

0.5

Ifbench(Google Research (2023))

0.4

Livecodebench(UC Berkeley + MIT + Cornell (2024))

0.2

Lcr(Artificial Analysis)

0.2

Scicode(UIUC + Argonne National Lab (2024))

0.2

Tau2(Sierra + U Toronto + Vector Institute (2025))

0.1

Aime(MAA (Mathematical Association of America))

0.1

Aime 25(MAA (Mathematical Association of America))

0.1

Terminalbench Hard(Stanford × Laude Institute (2026))

0.1

Hle(Center for AI Safety + Scale AI (2025))

0.0

LLM Stats 分類評分

(LLM Stats (zeroeval))

Image To Text

Instruction Following

Legal

Structured Output

Code

Math

Reasoning

Language

Multimodal

Finance

General

Healthcare

Tool Calling

Vision

Frontend Development

Agents

Economics

Physics

Biology

Chemistry

Long Context

Summarization

定價

輸入價格$0.8 / 1M tokens

輸出價格$3.2 / 1M tokens

混合價格(3:1)$1.4 / 1M tokens

快取讀取價格$0.2 / 1M tokens

速度

Tokens/秒0.0

首Token延遲0.00s

首回答延遲0.00s

供應商價格排行

2 個供應商

最便宜: Amazon最貴: Amazon Bedrock

供應商輸入輸出

1Amazon主要

$0.8

$3.2

2Amazon Bedrock

$0.8

$3.2

比較該模型在不同 API 供應商之間的定價。

外部連結

LLM Stats Artificial Analysis