SNPS

Prezzo Synopsys

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SNPS
$419,50
-$0,33(-0,07%)

*Data last updated: 2026-04-15 05:30 (UTC+8)

As of 2026-04-15 05:30, Synopsys (SNPS) is priced at $419,50, with a total market cap of $80,22B, a P/E ratio of 54,56, and a dividend yield of 0,00%. Today, the stock price fluctuated between $418,20 and $430,00. The current price is 0,31% above the day's low and 2,44% below the day's high, with a trading volume of 1,25M. Over the past 52 weeks, SNPS has traded between $376,18 to $651,73, and the current price is -35,63% away from the 52-week high.

SNPS Key Stats

Yesterday's Close$417,77
Market Cap$80,22B
Volume1,25M
P/E Ratio54,56
Dividend Yield (TTM)0,00%
Diluted EPS (TTM)6,87
Net Income (FY)$1,33B
Revenue (FY)$7,05B
Earnings Date2026-05-27
EPS Estimate3,17
Revenue Estimate$2,24B
Shares Outstanding192,03M
Beta (1Y)1.148

About SNPS

Synopsys, Inc. provides electronic design automation software products used to design and test integrated circuits. The company offers Fusion Design Platform that provides digital design implementation solutions; Verification Continuum Platform that provides virtual prototyping, static and formal verification, simulation, emulation, field programmable gate array (FPGA)-based prototyping, and debug solutions; and FPGA design products that are programmed to perform specific functions. It also provides intellectual property (IP) solutions for USB, PCI Express, DDR, Ethernet, SATA, MIPI, HDMI, and Bluetooth low energy applications; analog IP, including data converters and audio codecs; and system-on-chip (SoC) infrastructure IP, datapath and building block IP, and verification IP products, as well as mathematical and floating-point components, and Arm AMBA interconnect fabric and peripherals. In addition, the company offers logic libraries and embedded memories; configurable processor cores and application-specific instruction-set processor tools for embedded applications; IP subsystems for audio, sensor, and data fusion functionality; and security IP solutions. Further, it provides Platform Architect solutions for SoC architecture analysis and optimization; virtual prototyping solutions; and HAPS FPGA-based prototyping systems, as well as a series of tools used in the design of optical systems and photonic devices. Additionally, the company offers security testing, managed services, programs and professional services, and training that enable its customers to detect and remediate security vulnerabilities, and defects in the software development lifecycle, as well as manufacturing solutions. It serves electronics, financial services, automotive, medicine, energy, and industrial areas. The company was incorporated in 1986 and is headquartered in Mountain View, California.
SectorTechnology
IndustrySoftware - Infrastructure
CEOSassine Ghazi
HeadquartersSunnyvale,CA,US
Official Websitehttps://www.synopsys.com
Employees (FY)28,00K
Average Revenue (1Y)$251,93K
Net Income per Employee$47,57K

Synopsys (SNPS) FAQ

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Synopsys (SNPS) is currently trading at $419,50, with a 24h change of -0,07%. The 52-week trading range is $376,18–$651,73.

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Hot Posts su Synopsys (SNPS)

CryptoCommunityAggregation

CryptoCommunityAggregation

04-12 02:45
转一篇#英伟达# 的文章,英伟达已经不是一家公司而是一个AI帝国。 很多人还在把 NVIDIA 当成一家卖芯片的公司,但我越来越觉得,这种理解已经落后了。当我把这张投资版图拆开来看,一个更清晰的逻辑开始浮现:——这不是投资,这是在“布控整个 AI 需求链”。如果只看表面,你会觉得这是分散投资,但如果把所有节点连起来,会发现它们全部指向同一个终点:GPU 需求。 (1)先看最底层。$英特尔 INTC$ $新思科技 SNPS$ 这是芯片设计与制造能力,本质是确保整个半导体生态不会成为瓶颈。你可以理解为:就算未来竞争加剧,基础设计能力依然在体系内。 (2)再往上一层,是网络与光互联。$Lumentum LITE$ $COHR $MRVL 这些公司解决的是同一个问题——数据如何在 AI 集群之间高速流动。没有这一层,再强的 GPU 也会被带宽拖死。换句话说,这一层决定的是“算力能不能真正被用出来”。 (3)然后是最关键的一层——算力分发。$CRWV $NBIS 以及Nscale、Lambda 这一类 GPU 云厂商,本质是把 NVIDIA 的 GPU 变成“可租赁资源”,而不是一次性卖出去的硬件。这一步非常关键,因为它改变了商业模式:从卖设备 → 变成持续收租的生态。 (4)接下来是模型层。OpenAI、xAI、Mistral、Cohere、Perplexity 这一层才是“吃算力”的真正黑洞。所有模型公司,本质上都是 GPU 的最大消耗者。你会发现一个有意思的结构:NVIDIA 投的不是“一个赢家”,而是“所有可能成为赢家的人”。无论谁赢,GPU 都会被消耗。 (5)再往上,是应用与前沿场景。自动驾驶(Wayve)机器人(Figure AI)AI 制药($LLY、$RXRX)甚至核聚变(Commonwealth Fusion)这些看起来很分散,但本质只有一个:——它们会把 AI 从“软件”变成“现实世界需求”。一旦 AI 进入物理世界,算力需求不再是线性增长,而是指数级放大。这也是为什么 NVIDIA 的布局里会出现“看似不相关”的赛道。因为它押的不是行业,而是“需求爆发点”。 所以现在回到一个更核心的问题:为什么 NVIDIA 要投这么广?因为它在做一件非常少公司能做到的事——同时控制供给侧(芯片 + 网络 + 算力)同时布局需求侧(模型 + 应用 + 场景)这意味着什么? 意味着它不只是参与 AI 周期,而是在“放大 AI 周期”。很多人把 AI 看成一场竞赛,但 NVIDIA 的打法更像是:——不下注谁赢,而是确保每个人都必须用我的筹码。 当你从这个角度再看这张图,就会发现一个更深层的结构:每一笔投资,都在强化一个闭环:投资 → 需求增长 → GPU 消耗 → 收入提升 → 再投资这才是真正的飞轮。
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