SNPS

Synopsys Price

Closed
SNPS
$393,76
-$10,56(-%2,61)

*Data last updated: 2026-04-12 05:58 (UTC+8)

As of 2026-04-12 05:58, Synopsys (SNPS) is priced at $393,76, with a total market cap of $75,13B, a P/E ratio of 54,56, and a dividend yield of %0,00. Today, the stock price fluctuated between $389,15 and $407,20. The current price is %1,18 above the day's low and %3,30 below the day's high, with a trading volume of 1,60M. Over the past 52 weeks, SNPS has traded between $376,18 to $651,73, and the current price is -%39,58 away from the 52-week high.

SNPS Key Stats

Yesterday's Close$404,92
Market Cap$75,13B
Volume1,60M
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 Outstanding185,56M
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 $393,76, with a 24h change of -%2,61. The 52-week trading range is $376,18–$651,73.

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Hot Posts About Synopsys (SNPS)

CryptoCommunityAggregation

CryptoCommunityAggregation

3 hours ago
Turn an article from #英伟达#: NVIDIA is no longer just a company but an AI empire. Many still see NVIDIA as a chip-selling company, but I increasingly believe this understanding is outdated. When I break down this investment map, a clearer logic begins to emerge: — this isn't just investing, it's "orchestrating the entire AI demand chain." If you only look at the surface, you might think it's diversified investment, but if you connect all the nodes, you'll find they all point to the same endpoint: GPU demand. (1) First, look at the bottom layer. $Intel INTC$ $Synopsys SNPS$ This is the chip design and manufacturing capability, essentially ensuring that the entire semiconductor ecosystem won't become a bottleneck. You can think of it as: even if competition intensifies in the future, the fundamental design ability remains within the system. (2) Next, a layer above, is networking and optical interconnection. $Lumentum LITE$ $COHR $MRVL These companies solve the same problem — how data flows at high speed between AI clusters. Without this layer, even the strongest GPU would be bandwidth-limited. In other words, this layer determines whether "computing power can be truly utilized." (3) Then, the most critical layer — compute distribution. $CRWV $NBIS and GPU cloud providers like Nscale, Lambda, essentially turn NVIDIA's GPUs into "rentable resources" rather than hardware sold once. This step is crucial because it changes the business model: from selling devices → to a continuous leasing ecosystem. (4) Next is the model layer. OpenAI, xAI, Mistral, Cohere, Perplexity This layer is the real black hole for "computing consumption." All model companies are fundamentally the biggest consumers of GPUs. You'll notice an interesting structure: NVIDIA isn't investing in "one winner," but in "all potential winners." No matter who wins, GPUs will be consumed. (5) Moving up, are applications and frontier scenarios. Autonomous driving (Wayve), robotics (Figure AI), AI in pharmaceuticals ($LLY, $RXRX), even nuclear fusion (Commonwealth Fusion). These may seem scattered, but fundamentally, there's only one: — they turn AI from "software" into "real-world demand." Once AI enters the physical world, the demand for computing power no longer grows linearly but exponentially. This is also why NVIDIA's layout includes "seemingly unrelated" tracks. Because it bets not on an industry, but on the "demand explosion point." So now, returning to a more core question: why is NVIDIA investing so broadly? Because it is doing something very few companies can — simultaneously controlling the supply side (chips + networking + compute) and laying out the demand side (models + applications + scenarios). What does this mean? It means it’s not just participating in the AI cycle but "amplifying the AI cycle." Many see AI as a competition, but NVIDIA's approach is more like: — not betting on who wins, but ensuring everyone must use my chips. Looking at this map from this perspective reveals a deeper structure: every investment reinforces a closed loop: Investment → Demand growth → GPU consumption → Revenue increase → Reinvestment — this is the true flywheel.
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