Nvidia

Chip giant Nvidia Corp on Tuesday unveiled its new computing platform called DRIVE Thor that would centralize autonomous and assisted driving as well as ...

"There's a lot of companies doing great work, doing things that will benefit mankind and we want to support them," Shapiro said. ban on exports of two top Nvidia computing chips for data centers to China. [read more](/business/autos-transportation/upset-by-high-prices-gms-cruise-develops-its-own-chips-self-driving-cars-2022-09-14/) Register now for FREE unlimited access to Reuters.com [(GM.N)](https://www.reuters.com/companies/GM.N) autonomous driving unit Cruise last week said it had developed its own chips to be deployed by 2025.

TSMC apple bionic TSMC snapdragon TSMC ryzen And TSMC nvidia. What are you going to do guys without TSMC ? Reply. F. FatShady; CLs; 22 minutes ago.

Thats enough for me to lose interest on gaming and PC building. [Feem, 4 hours ago](#2588273)@PMKLR3m Yeah, the contract between EVGA and Nvidia got terminated and EVGA said it was becau... [more](#2588273)Nvidia became too much greedy towards partners and with no support at all; for example the price of GPU is declining and Nvidia is undercutting the partners by dropping the price without any information for the OEM ... Dont waste your money on ngredia,who forget about u for the past 4 years and focus on GPU mining. [GregLu, 4 hours ago](#2588292)Nvidia became too much greedy towards partners and with no support at all; for example the pri... [Anonymous, 4 hours ago](#2588275)Euro prices make me sad, and if nvidia didn't lie like with 3000 series, we can add anoth... :( [more](#2588298)I don't know about AMD and their partner/relation but if you have news, I'm all ears. - 👍 [GregLu, 1 hour ago](#2588368)I don't know about AMD and their partner/relation but if you have news, I'm all ears... - Anonymous - xhm

Are graphics cards like the just-revealed RTX 4090 and RTX 4080s becoming unaffordable?

I hope there is some sort of relief on the horizon, because as the one Redditor put it, “I love PC gaming, but I can’t fucking afford to be a part of it anymore.” The RTX 4080 16GB is 3x the performance of the RTX 3080 Ti on next-gen content like Cyberpunk with RT Overdrive mode or Racer RTX—for the same price of $1199. But viewing events from the consumer side, it really feels like the costs of enthusiast PC gaming are continuing to skyrocket, and at a time when the costs of just about everything else are, too. The price point of RTX 4090 starts at $1599. Of course, even then its MSRP is $899, which is $400 more than the RTX 3070’s original MSRP of $499. Now Nvidia’s revealed a 16GB RTX 4080, which many observers take to be the closest to a true 3080 successor, for a whopping $1199—an increase of $500. They are trying to sell you a 4070 rebranded as a 4080 for 900$ lmao.” [One commenter looked back](https://old.reddit.com/r/hardware/comments/xjbobv/geforce_rtx_4090_revealed_releasing_in_october/ip7pdmc/) to 2018’s GeForce 10-series to pinpoint why today’s prices felt so exorbitant. [a ray-traced version of Portal](https://www.nvidia.com/en-us/geforce/news/portal-with-rtx-ray-tracing/). For example, the RTX 2070 cost almost as much as the prior high-end GTX 1080, despite being less of a flagship card. With the 20 series, they bumped all of the prices a whole fucking tier, and it looks like they are doing it again. Indeed, in 2018, Nvidia attracted criticism for pricing its then-new RTX 20-series cards a full “tier” higher than the previous 10-series cards had cost. Today, after many months of leaks, rumors, and speculation, Nvidia finally officially revealed its next generation of graphics cards, the RTX 4000 series.

Nvidia promises to make 3D modeling and digital technology more accessible for your data center, just not at the moment.

We in the data center industry know what that means, more demand for access to storage, network, and computer. Systems to support the chips are coming in the first half of 2023. The implementation of robotics to maintain data center equipment would get a boost from NVIDIA’s Omniverse, based on case studies from other verticals such as the automotive and railway industries. We admit, many of the firm’s announcements have a decided cool factor, leveraging the power of 3D for realistic simulations, but is there anything here that will change your life as a data center pro today or in the very near future? We're seeing a trend here in that NVIDIA wants simulation technology to be readily available and as plug-and-play as possible for enterprises. Our friends at Siemen’s provided us with access to a [webinar on digital twin technology](https://new.siemens.com/global/en/markets/data-centers/events-webinars/webinar-digital-twin-applications-for-data-centers-apac-emea.html).

Team Green also announced the RTX 4080 starts at $899, though we don't know a release date.

Still, Nvidia’s RTX 4080 is also here if $1,599 seems too costly, and Huang said the company will continue to support its RTX 3000 line as well. Taken together with the RTX 4090's hardware, Nvidia promises its new card will be 2x faster at non ray-tracing tasks and 4 time faster at ray-tracing ones. Huang demonstrated how it works with The Elder Scrolls III: Morrowind, a game from 2002, and while we don’t know much about what kind of power it will need in addition to an RTX 4000 series GPU, it’s going to be available for modders everywhere. With blanket promises that the card is 2-4 times faster than the RTX 3090 Ti, which is an upgraded version of the 3090, Huang showed 4K framerates above 100 fps on both Cyberpunk 2077 and Microsoft Flight Sim, both with ray-tracing on. Which is good, because the RTX 4090 looks like a significant improvement over the RTX 3090, and especially over any GTX 1000 or RTX 2000 series GPUs you might still be rocking. To support that dream, the company also announced DLSS 3.0 upgraded tech that supplies more frames with less work, plus SER, a new RTX graphics engine that promises to drastically increase ray tracing performance.

After much anticipation, NVIDIA finally unveiled the next-gen GeForce RTX 40 Series GPUs. Promptly called the RTX 4090 and RTX 408.

There will be two RTX 4080 configurations - the 16GB model is $1,199 (~RM5477) featuring 9,728 CUDA cores and 16GB of high-speed Micron GDDR6X memory. In terms of pricing and availability, the RTX 4090 will be launching on 12 October starting from $1,599 (~RM7304) whereas the RTX 4080 will come in November. On top of that, the latest version of NVIDIA DLSS technology is also introduced on Ada, alongside DLSS 3.

(Sept 20): Nvidia Corp on Tuesday announced new flagship chips for video gamers that use artificial intelligence (AI) to enhance graphics, saying it has ...

The Lovelace chips have extended that technique to generate entire frames of a game using AI. The new Lovelace chips use AI to improve video game graphics. Nvidia has gained attention in recent years with its booming data centre business, which sells chips used in artificial intelligence work such as natural language processing.

The H100 Tensor Core GPU is in full production, and the first servers based on Nvidia's new Hopper architecture are due next month.

Language models are tools trained to predict the next word in a sentence, such as autocomplete on a phone or browser. [GPUs](https://www.networkworld.com/article/3659836/the-three-way-race-for-gpu-dominance-in-the-data-center.html) is in full production, with global partners planning to roll out products and services in October and wide availability in the first quarter of 2023. [Hopper](https://www.networkworld.com/article/3673256/nvidia-hopper-gpu-slays-predecessor-in-ml-benchmarks.html) features a number of innovations over Ampere, its predecessor architecture introduced in 2020. Lastly, Hopper has the fourth-generation NVLink, Nvidia’s high-speed interconnect technology that can connect up to 256 H100 GPUs at nine times higher bandwidth versus the previous generation. “Our customers are looking to deploy data centers that are basically AI factories, producing AIs for production use cases. Partners include Atos, Cisco, Dell, Fujitsu, Gigabyte, HPE, Lenovo and Supermicro.

At the top of the stack is the new RTX 4090. This massive new GPU features 16384 CUDA cores with boost clocks that go up to 2.52GHz. The card comes with 24GB of ...

Compared to the 40 shader-TFLOPs of the RTX 3090 Ti, the RTX 4090 has 83-TFLOPS. At the heart of these new graphics cards is the new GPU. It's part of the Nvidia RTX Remix modding platform, which features tools for improving the visuals of older titles. At the top of the stack is the new RTX 4090. The RTX 4090 has a power rating of 450W and runs on a single 16-pin PCIe Gen 5 or 3x 8-pin PCIe cables. Nvidia claims it is 2-4x faster than the RTX 3090 Ti.

In his GTC keynote today, Nvidia CEO Jensen Huang launched another new Nvidia GPU architecture: Ada Lovelace, named for the legendary mathematician regarded ...

There is also Omniverse Replicator, a 3D synthetic data generator for researchers, developers, and enterprises that integrates with Nvidia’s AI cloud services. Omniverse Cloud will also be available as Nvidia managed services via early access by application. “Using this technology to generate large volumes of high-fidelity, physically accurate scenarios in a scalable, cost-efficient manner will accelerate our progress towards our goal of a future with zero accidents and less congestion.” “Planning our factories of the future starts with building state-of-the-art digital twins using Nvidia Omniverse,” said Jürgen Wittmann, head of innovation and virtual production at BMW Group. With Omniverse Cloud, users can collaborate on 3D workflows without the need for local compute power. “In the case of OVX, we do optimize it for digital twins from a sizing standpoint, but I want to be clear that it can be virtualized. Nvidia said that the RTX 6000 would be available in a couple of months from channel partners with wider availability from OEMs late this year into early next year to align with developments elsewhere in the industry. The second generation OVX system features an updated GPU architecture and enhanced networking technology. Ada Lovelace is not a subset of Nvidia’s Hopper GPU architecture (announced just six months prior), nor is it truly a successor — instead, Ada Lovelace is to graphics workloads as Hopper is to AI and HPC workloads. “With a massive 48GB frame buffer, OVX, with eight L40s, will be able to process giant Omniverse virtual world simulations.” The company also announced two GPUs based on the Ada Lovelace architecture — the workstation-focused RTX 6000 and the datacenter-focused L40 — along with the Omniverse-focused, L40-powered, second-generation OVX system. In his GTC keynote today, Nvidia CEO Jensen Huang launched another new Nvidia GPU architecture: Ada Lovelace, named for the legendary mathematician regarded as the first computer programmer.

The 'Ada Lovelace' series is unaffected by US ban on selling top data centre chips to China.

The CNBC Investing Club gives investors a behind-the-scenes look at how Jim Cramer manages an investment portfolio so you can manage your own money and ...

"The actions we're taking right now to clear the inventory in the channel, to normalize inventory in the channel, is a good action. See here for a full list of the stocks.) As a subscriber to the CNBC Investing Club with Jim Cramer, you will receive a trade alert before Jim makes a trade. "Coming into the year, the whole market was really, really vibrant and was super high, and the supply chain was super long, so we had a lot of inventory in the pipeline," Huang said. Huang estimated that, in total, these corrective actions should span about two-and-a-half quarters, meaning the impact would be felt in "a little bit of Q4." "Of course, that resulted in Q2 and Q3 being a lot lower than we originally anticipated, but the overall gaming market remains solid," he added. "The world's gaming market continues to be vibrant, and we have absolutely no doubt that when Ada gets into the marketplace there's going to be lots of excited gamers waiting for it," Huang said.

Today at the company's fall 2022 GTC conference, Nvidia announced the NeMo LLM Service and BioNeMo LLM Service, which ostensibly make it easier to adapt LLMs ...

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Nvidia announced Drive Thor, an ambitious centralized car computer cluster to unify functions for automated driving and in-car infotainment to first appear ...

Next-gen system-on-a-chip centralizes all intelligent vehicle functions on a single AI computer for safe and secure autonomous vehicles. September 20, 2022 by ...

DRIVE Thor marks the first inclusion of a transformer engine in the AV platform family. The SoC is capable of multi-domain computing, meaning it can partition tasks for autonomous driving and in-vehicle infotainment. Manufacturers can configure the DRIVE Thor superchip in multiple ways. Rather than relying on these distributed ECUs, manufacturers can now consolidate vehicle functions using DRIVE Thor’s ability to isolate specific tasks. With 8-bit floating point (FP8) precision, the SoC introduces a new data type for automotive. The automotive-grade system-on-a-chip (SoC) is built on the latest CPU and GPU advances to deliver 2,000 teraflops of performance while reducing overall system costs.

Alongside its GeForce RTX 40 Series, NVIDIA also announced the RTX 6000, its new powerhouse workstation GPU base on the same architecture.

As for how much the RTX 6000 is going to set you back, that actually remains the million-dollar question. That GPU is the RTX 6000 and like its predecessors in the same lineup, it is a workstation graphics card, made and built to help professionals working in fields of design or simulation. As for how much graphics memory the RTX 6000, the GPU gets a whopping 48GB of GDDR6 memory.

NVIDIA introduced NVIDIA DRIVE Thor, its next-generation centralized computer for safe and secure autonomous vehicles. DRIVE Thor, which achieves up to 2000 ...

The DRIVE Thor SoC and AGX board are developed to comply with ISO 26262 standards. With this engine, DRIVE Thor can accelerate inference performance of transformer deep neural networks by up to 9x, which is paramount for supporting the massive and complex AI workloads associated with self driving. Another advantage of DRIVE Thor is its 8-bit floating point (FP8) capability. DRIVE Thor with MIG support for graphics and compute uniquely enables IVI and advanced driver-assistance systems to run domain isolation, which allows concurrent time-critical processes to run without interruption. DRIVE Thor supports multi-domain computing, isolating functions for automated driving and IVI. DRIVE Thor, which achieves up to 2,000 teraflops of performance, unifies intelligent functions—including automated and assisted driving, parking, driver and occupant monitoring, digital instrument cluster, in-vehicle infotainment (IVI) and rear-seat entertainment—into a single architecture for greater efficiency and lower overall system cost.

Nvidia RTX 6000 'Ada Lovelace' workstation GPU promises to boost performance by changing the way viewports and scenes are rendered.

However, Nvidia also dedicated some time to engineering simulation, specifically the use of Ansys software, including Ansys Discovery and Ansys Fluent for Computational Fluid Dynamics (CFD). With Shader Execution Reordering (SER), the Nvidia RTX 6000 dynamically reorganises its workload, so similar shaders are processed together. Nvidia DLSS has been around for several years and with the new ‘Ada Lovelace’ Nvidia RTX 6000, is now on its third generation. It processes the new frame, and the prior frame, to discover how the scene is changing, then generates entirely new frames without having to process the graphics pipeline. The Nvidia RTX 6000 is a dual slot graphics card with 48 GB of GDDR6 memory (with error-correcting code (ECC)), a max power consumption of 300 W and support for PCIe Gen 4, giving it full compatibility with workstations featuring the latest Intel and AMD CPUs. It is not to be confused with 2018’s Turing-based [Nvidia Quadro RTX 6000](https://aecmag.com/features/nvidia-takes-giant-leap-with-real-time-ray-tracing/).

AI technology company Nvidia showcased a high-performance automotive computer designed to advance processing of in-vehicle entertainment and automated driving ...

[Qualcomm](https://www.autonews.com/suppliers/qualcomm-wants-larger-role-autos) hasn't yet announced the processing speed of its latest Snapdragon Digital Chassis. Analysts say the computer is designed to keep Nvidia ahead of rival Intel and its Mobileye automotive chip subsidiary. [Nvidia](https://www.autonews.com/suppliers/nvidias-huang-predicts-software-will-rule-industry) showcased a high-performance automotive computer designed to advance processing of in-vehicle entertainment and automated driving functions.

NVIDIA has presented the Jetson Orin Nano series, a pair of system-on-modules (SOM) that supposedly deliver up to 80x the performance of the original Jetson ...

On the other hand, the Jetson Orin Nano 8GB has not only double the RAM, but also a 128-bit memory bus with a 68 GB/s bandwidth. On the one hand, there is the Jetson Orin Nano 4GB, which has a 512-core Ampere architecture GPU with 16 Tensor cores and a peak 625 MHz clock speed. Incidentally, the 4 GB model operates at between 5 W and 10 W, compared to the 7 W to 15 W that its 8 GB sibling consumes. Also, the 8 GB model has double the GPU capabilities and AI performance, albeit with the same 625 MHz GPU clock speed. NVIDIA adds that both SOMs measure 69.6 x 45 mm, thereby conforming to the 260-pin SO-DIMM connector standard. Supposedly 80x faster than the original Jetson Nano that arrived in 2019, the Jetson Orin Nano will be available in two variants at different price points.

CHATSWORTH, Calif., Sept. 21, 2022 – DDN, a global leader in artificial intelligence (AI) and multi-cloud data management solutions, today announced its ...

DDN provides its enterprise customers with the most flexible, efficient and reliable data storage solutions for on-premises and multi-cloud environments at any scale. [DDN](https://www.ddn.com/) is the world’s largest private data storage company and the leading provider of intelligent technology and infrastructure solutions for enterprise at scale, AI and analytics, HPC, government, and academia customers. DDN’s A3I AI400X2 is an all-NVMe appliance designed to help customers extract the most value from their AI and analytics data sources, is proven in production at the largest scale and is the world’s most performant and efficient building block for AI infrastructures. Registration is free and open to all — [click here](https://www.ddn.com/company/events/gtc-fall-2022) for more information about DDN at GTC. [Selene and Beyond: Solutions for Successful SuperPODs](https://www.nvidia.com/gtc/session-catalog/?tab.catalogallsessionstab=16566177511100015Kus&search=ddn#/session/1658500849998001YbEc).” The session will focus on how DGX SuperPOD users can best manage their infrastructure even at extreme scales. Backed by DDN, the leader in AI data management, along with NVIDIA technology, extensive integration and performance testing, customers can rest assured that they will get the fastest path to AI innovation. [DDN](https://www.ddn.com/), a global leader in artificial intelligence (AI) and multi-cloud data management solutions, today announced its next generation of [reference architectures](https://www.ddn.com/products/a3i-accelerated-any-scale-ai/#reference-architectures) for [NVIDIA DGX BasePOD](https://www.nvidia.com/en-us/data-center/dgx-basepod/) and [NVIDIA DGX SuperPOD](https://www.nvidia.com/en-us/data-center/dgx-superpod/). Customers using these DGX BasePOD configurations will not only get integrated deployment and management, but also software tools including the NVIDIA AI Enterprise software suite, tuned for their specific applications in order to speed up developer success. “Our close technical and business collaboration with NVIDIA is enabling enterprises worldwide to maximize the performance of AI applications and simplify deployment for all,” said Dr. “Organizations modernizing their business with AI need flexible, easy-to-deploy infrastructure to address their enterprise AI challenges at any scale,” said Tony Paikeday, senior director of AI systems, NVIDIA. “With this next generation of reference architectures, which include DDN’s A3I AI400X2, we’re delivering significant value to customers, accelerating enterprise digital transformation programs, and providing ease of management for the most demanding data-intensive workloads.” [DDN deployed more than 2.5 exabytes of AI storage in 2021 and is now supporting thousands of ](https://6lli539m39y3hpkelqsm3c2fg-wpengine.netdna-ssl.com/wp-content/uploads/2021/03/ddn-logo_175x63.png) [NVIDIA DGX systems](https://www.ddn.com/partners/nvidia-global-solution-partners/) deployed around the world.

Nvidia's basic DGX POD reference architecture specifies up to nine Nvidia DGX-1 servers, 12 storage servers (from Nvidia partners), and three networking ...

It includes Nvidia DGX Foundry, which features the Base Command software and NetApp Keystone Flex Subscription. In other words, Nvidia’s success with its DGX POD architectures is proving to be a great tailwind for storage suppliers like DDN. It says that scaling capacity and performance is as simple as adding DGX systems, networking connectivity, and Weka nodes. By adding additional storage nodes, the architecture can grow to support more DGX A100 systems. The DGX systems are GPU server-based configurations for AI work and combine multiple Nvidia GPUs into a single system. Nvidia says BasePOD includes industry systems for AI applications in natural language processing, healthcare and life sciences, and fraud detection.

The company plans on going down the RTX 4000 stack over time, according to Nvidia's CEO.

Why Nvidia is ignoring the mid-tier and low-end market for now is "simple" and "not so complicated," Jensen said. [oversupply situation](https://www.pcmag.com/news/nvidia-decreased-demand-means-gpu-price-cuts) with its older RTX 3000 series. That’s because the 12GB model not only has less video memory, it also contains only 7,680 CUDA cores. "We usually start at the high end because that’s where the enthusiasts want a refresh first. But over time, we’ll get other products in the lower-ends of the stack out to the market.” The statement also signals that RTX 4000 GPUs will eventually arrive at more consumer-friendly price points.

At its GTC developer event, Nvidia introduces new cloud services, for custom training of LLMs and biomedical research on LLM protein models.

“The ability to tune foundation models puts the power of LLMs within reach of millions of developers who can now create language services and power scientific discoveries without needing to build a massive model from scratch.” Users of these cloud services and APIs gain access to massive LLMs, including Megatron 530B (so named because it has 530 billion training parameters) without needing possession of the model or any GPU hardware, be it on-premises or in the cloud. Nvidia says the prompt training times range from minutes to hours, a trivial duration compared to the weeks-to-months training times required for the LLMs themselves. It turns out that even fully-trained LLMs can be used for a range of use cases (including those beyond language learning), as long as their massive foundation training is augmented with some additional special training, on a customer’s own data. [GPU Technology Conference](https://www.nvidia.com/gtc/) (GTC) developer event today, Nvidia is announcing two new cloud services based on [Large Language Models (LLM)](https://thenewstack.io/5-ai-trends-to-watch-out-for-in-2022/) technology. That architecture is based on the premise that “AI can understand which parts of a sentence or which parts of an image, or even very disparate data points, are relevant to each other.” Kharya also said transformers can even train on unlabeled data sets, which expands the volume of data on which they can be trained.

Nvidia CEO Jensen Huang unveiled the GeForce RTX 40 Series GPU at the Fall GTC conference. Company also announces first Omniverse SaaS cloud service, AI ...

In addition, Amazon Web Services, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure will start deploying H100-based instances in the cloud starting next year. To power these AI applications, Nvidia will start shipping its NVIDIA H100 Tensor Core GPU, with Hopper’s next-generation Transformer Engine, in the coming weeks. The GeForce RTX 4080 will in November with two configurations. The GeForce RTX will come in several configurations. During the presentation, Huang put the new GPU through its paces in a fully interactive simulation of Racer RTX, a simulation that is entirely ray traced, with all the action physically modeled. Nvidia CEO Jensen Huang, in a keynote speech, said the GPUs would provide a substantial performance boost that would benefit developers of games and other simulated environments.

Nvidia Corp CEO Jensen Huang holds one of the company's new RTX 4090 chips for computer gaming in this undated handout photo provided September 20, 2022.

See here for a full list of the stocks.) As a subscriber to the CNBC Investing Club with Jim Cramer, you will receive a trade alert before Jim makes a trade. Bottom line In the end, we think Nvidia's pricing is as much about clearing out inventory as it is inflation and think the higher sticker, while perhaps frustrating to consumers, is a good sign for shareholders as it should help us get through the inventory glut more quickly and speaks to higher revenue potential in the next up cycle. So, in addition to adjusting for inflation, the pricing on the low end may also be a strategic way to flush out retail channel inventory ahead of the holiday selling season. The first reason has to do with accounting for a decades-high inflationary environment, and the second reason has to do with using the price differential to flush out excess inventory of 30 series GPUs to make room for the next-generation cards based on the just-announced Ada Lovelace architecture, which start hitting the market next month. While those with the cash that demand the latest and greatest will no doubt go for the new 40 series chips, most gamers and creators may instead opt for the 30 series, which still offer great performance but are also now seeing steep discounts at retailers as Nvidia and channel partners look to flush out inventory ahead of the 40 series hitting shelves. Put another way, if we were to adjust for inflation, a comparable 40 series price tag (think 2020 dollars) would be about $770 for the 4080 and $1,650 for the 4090.

It's not the capabilities of these cards that were called into question, but their pricing. The RTX 4090 will arrive with a $1,599 price tag, followed by $1,199 ...

Be that as it may, it’s sad to hear a confirmation that the prices will continue following an upward trend. It makes sense to price the After the GPU shortage has subsided, Nvidia and its partners were left with an oversupply of graphics cards. Huang cited the rising costs of components and slowing of additional power as driving forces behind high GPU prices. [These prices are too steep](https://www.digitaltrends.com/computing/why-people-are-upset-about-rtx-4090-and-4080/), all things considered, but it now seems that this might be the new normal. The idea that the chip is going to go down in price is a story of the past,” said Nvidia CEO Jensen Huang in a response to PC World’s Gordon Ung.

Nvidia recently announced the RTX 4000 Series of graphics cards, calling into question whether its predecessors are still worth buying.

However, the latest RTX 4080 comes with improved architecture, boasting a 4nm node instead of Ampere’s 8nm node. The RTX 4080 12GB has 7,680 CUDA Cores, while the 16GB model comes with 9,728 CUDA Cores. However, thanks to the improved architecture and new updated software, it looks like it will be a close contest. However, the RTX 3090 comes with a staggering 24GB of memory, making it the superior option if memory is a priority for you. And looking at the graph below, we can see that Ada Lovelace offers massive performance boosts over Ampere. It also brings in the latest [Lovelace](https://www.trustedreviews.com/explainer/what-is-nvidia-lovelace-4268040) architecture, alongside new features exclusive to the RTX 4000 Series, such as 3rd-generation ray tracing and [DLSS](https://www.trustedreviews.com/explainer/what-is-dlss-4110546) 3. However, we can use the specs provided by Nvidia to get an idea of which graphics card will come out on top. CUDA Cores are developed by Nvidia and are designed to take on multiple calculations at the same time, allowing for speedy and efficient parallel computing. With all these new features and new architecture, is the RTX 3000 Series still worth it? The RTX 4080 will be available to purchase at some point in November this year, with no specific dates being singled out yet. More transistors generally result in a faster performance, as the data can be transferred and processed at a faster rate. More cores mean that more calculations can be done at once, which is important for anyone looking to play graphically demanding games.

'The idea that a chip is going to go down in cost over time, unfortunately, is a story of the past,' Nvidia CEO Jensen Huang says one day after the company ...

[wafer](https://www.pcmag.com/encyclopedia/term/wafer) is a lot more expensive today than what it was yesterday. That said, it seems a lot of the performance gains will tap AI-based software acceleration techniques to improve frame rates and “But at the same price point, our value delivered generational is off the charts, and remains off the charts this time," he added. Blame the death of [Moore’s Law](https://www.pcmag.com/encyclopedia/term/moores-law) and rising component costs, says CEO Jensen Huang. “The numbering system is just a numbering system,” he added. So that’s really the basis to look at —at the same price point,” Huang said. And the ability for Moore’s Law to deliver twice the performance at the same cost, or at the same performance half the cost every year-and-a-half, is over. Instead, it’s better to compare the products by looking at their retail value when they first went on sale. Rather, it’s best compared to an $1,199 However, Huang says consumers have to readjust their expectations around GPU pricing, pointing to the hefty manufacturing costs involved in chip-making. Then the cards scale up to the $1,199 RTX 4080 16GB model and $1,599 RTX 4090, which arrives next month. The most affordable model, the GeForce RTX 4080 12GB model, starts at $899.

When queried over high PC GPU prices, Nvidia's Jensen Huang said 'Moore's Law is dead'

Now, Nvidia is signaling its intent to keep the price squeeze on consumers as well, and with prices this high, we’re in uncharted waters. [sticker shock from Nvidia’s reveal of astronomical prices](https://kotaku.com/pc-nvidia-rtx-4090-4080-gpu-card-prices-crypto-scalping-1849560018) for its new 4000-series graphics cards yesterday gave you disadvantage on perception checks, I bring bad news: It’s not likely to get any better, at least as far as Nvidia is concerned. Yesterday, an Nvidia spokesperson told Kotaku that, “RTX 3080 10GB is still an incredible value and we’ll continue to offer it in our lineup.”