Nvidia has just launched its missile against Intel AMD’s dominance in PCs and laptops. There is a problem: it is a slightly obsolete missile

In October 2025 Nvidia launched its DGX Sparka unique workstation that the company called “the world’s smallest AI supercomputer.” that machine It was actually announced in January.but it took a while to reach the market. When it finally did, it became an interesting alternative but somewhat limited in scope. That is just what the new Nvidia RTX Spark family, which will arrive, wants to change both in the form of laptops as desktop computers, and that it will do so with a fundamental difference: Windows for ARM. Hello, Windows for ARM. The golden DGX Spark were Linux-based workstations, which targeted them at a smaller audience, but with the RTX Spark, Nvidia wanted to make the big leap to the general public. These devices are based on Windows 11 for ARM, and will take advantage of all hardware and software capabilities so that this technological solution is no longer only aimed at AI enthusiasts. Of course, that will continue to be one of the segments it will target, but these systems can also be used for both creative and gaming environments. In Xataka We wanted an ideal PC to be able to experiment with local AI models. The Framework Desktop is the answer to our prayers Approximate performance: an RTX 5070. Those responsible for NVIDIA have not yet given too many specific details about what we can expect from this platform in terms of performance, but they have indicated that the performance of the GPU It is close to that of an RTX 5070 (portable version), although the exact numbers depend on the specific application or game: in some it will be a little better, in others a little worse and in others exactly the same. Yes, they have indicated that the promise is to obtain 100 FPS in 1440p gaming as reference data. Same chip, different operating system. Hardware technical specifications They are identical to those of the DGX Spark. The main data are the following: NVIDIA Grace Blackwell Architecture CPU: up to 20 Grace cores GPU: Developed in collaboration with MediaTek, up to 6,144 CUDA cores, 1 PFLOP of AI performance Unified memory: up to 128 GB LPDDR5X at 273 GB/s with NVLink at 600 GB/s But compared to the DGX Spark, we insist, the fundamental difference is that instead of using a specific Nvidia Linux distribution for these machines, here we can take advantage of Windows 11 for ARM. When AI controls your computer. During the presentation of this platform, those responsible for Nvidia talked about the absolute rise of AI agents and how this will mark a paradigm shift in the way we use our PCs and laptops. Before we did it with a mouse and keyboard, but they see a near future in which control is taken by those AI agents, with whom we will interact in a quite different way. The example is the already famous OpenClaw and Hermeswhich with the appropriate permissions can run all kinds of tasks and applications on the computer to autonomously do things for us. Six laptops initially. The Nvidia RTX Spark platform will initially be available in six devices from six different manufacturers that will rely on this technological solution from launch. ASUS, Dell, HP, Lenovo, Microsoft and MSI will have their equipment ready this fall, although at the moment there are no specific specifications or prices announced. It is possible that during Computex we will learn more details about these devices. What can we expect in autonomy. At the moment no specific data has been given about the efficiency of these devices, but Nvidia spoke of a battery life “for the whole day.” They highlight the efficiency of the GPU and in fact indicate that GPU performance will be virtually the same whether the laptop is plugged in or not. Obviously in intensive tasks and demanding games that battery will drain much more quickly. In Xataka Goodbye to the duopoly of Intel and AMD in Windows: the arrival of NVIDIA processors is imminent and brings 8 laptops under its arm The doubt of Windows for ARM. The commitment to Microsoft’s operating system is striking, but Nvidia believes that now the system is much more mature, and that both emulation and hardware support It’s much better than in the past thanks to the work that Microsoft and Nvidia have done in the months and years leading up to this launch. They talk about a “first-class experience” for the operating system, and even commented that they have worked with the developers of anti-cheat systems in video games so that this is not a problem on these computers. And also desktop computers. When Nvidia announced its DGX Spark, then similar desktop computers appeared in format that also offered that same platform. The same thing will happen with RTX Spark, and although there was hardly any data here, Nvidia did indicate that these devices will appear in the fall from Acer, Asus, Dell, Gigabyte, HP, MSI and Lenovo. {“videoId”:”x7ztphf”,”autoplay”:false,”title”:”How to know the components of your PC (RAM, Graphics, CPU…) and the state they are in”, “tag”:”webedia-prod”, “duration”:”387″} Many unknowns and certain obsolescence. There are many doubts surrounding these devices in terms of performance or price, but there is another fundamental problem: when these laptops and desktop PCs appear starting in the fall, they will do so with chips that have been on the market for a year and therefore in a certain sense are already somewhat obsolete. Competing with the Desktop Framework. The memory bandwidth is not exceptional, and for example the Framework Desktop presented in August 2025 already offered a similar configuration in that section, with up to 128 GB of LPDDR5x memory at 256 GB/s. It will be interesting to see how the RTX Spark machines perform against alternatives like this (which makes use of a “traditional” x86 Windows 11 operating system) and whether Nvidia’s ARM chip can really make a difference in an ultra-competitive market. In Xataka |The demand for AI memories is suffocating mobile manufacturers. The largest … Read more

AMD’s problem is not that it does not make good gpus for ia. Is that it is not even close to Nvidia

AMD is doing things well, but even doing them still unable to compete with Nvidia. The company has just raised its renewed road map with promising models, but that is not a guarantee of anything to a NVIDIA that will not let its absolute leadership position escape. The problem for AMD is not to be, but get others to take note. IDC consultancy data indicate that Nvidia dominates the AI ​​chips market with 85.2% market dick, for 14.3% AMD. Other analysts like Jon Pedie Research go beyond and According to your data The NVIDIA quota in this segment is 92%. AMD instinct mi350 are just the beginning. The GPUS for IA, which AMD calls “accelerators”, follow its evolution. During the event they presented their family or Instinct Mi350 series with two variants, MI350X and MI355X. According to the manufacturer, these chips are four times higher in general performance with respect to the previous generation, but are up to 35 times more powerful in the field of inference AI (that is, in the practical use of models such as Chatgpt, which “infers” “their responses from our prompts). They have 288 GB of HBM3E memory and a memory bandwidth of 8 TB/s. Its yield is 18.45 pflops in FP4 precision and 9.2 pflops in precision FP8. Instinct Mi400 in 2026. Next year the new family of AMD’s accelerators will arrive. It’s about future MI400 instinctwhich will arrive with up to 432 GB of HBM4 memory, 19.6 TB/s of bandwidth of that memory, and a performance of 40 pflops in precision FP4 and 20 Pflops in precision FP8. These monsters will be sold in future racks with infrastructure “Helios“, that You can house Up to 72 Mi400 with up to 260 TB/s total bandwidth thanks to its interconnection technology, Ultra Accelerator Link. EPYC VENICE. AMD not only talked about GPUS: it also has its future processors for servers in data centers in full development. The Epyc Venice will arrive in 2026 and will be based on Zen 6 architecture. Among the variants, an especially spectacular with 256 cores that will offer up to 70% more performance compared to the previous generation. These processors will be built with future MI400 instinct. They are expected to be manufactured with the N2P (2 Nm) node of TSMC. Helios against Oberon. The aforementioned Rack Helios will compete with not already with the current Nvidia AI server, the GB200 NVL72 which connects 36 CPUS Grace and 72 Gpus Blackwell. He is destined to compete with his successor, which has Oberon’s code name and will use IA B300 GPUS with Vera Rubin architecture. The yields and benefits of these future racks are absolutely dizzy, and for example their Precision Power FP8 is 1.4 Exaflops. The same in some things, better in others. AMD promises to match NVIDIA in several sections, but also ensures that it will exceed it remarkably (50% more) in memory quantity and width, something crucial for training and inference AI. Be careful, because at the end of 2027 NVIDIA prepares the Rubin Ultra architecture, which promises racks with up to 5 Exaflops in FP8 precision, three times more than Helios or Oberon. In 2027 we will have another “summer”. The AMD roadmap goes further, and they have already prepared the development of their new generation of chips for summer Epyc servers, which will replace the Epyc Venice. These CPUS will be paired with the future MI500X instinct, and it is expected – although it is not safe – that both types of chip take advantage of the one already announced TSMC A16 node (1.6 Nm), which will begin to be used at the end of 2026. There are no specifications for these developments, surely because they will depend on the manufacturing node that AMD ends up using to produce them. Frantic race. All these ads show that AMD does not want to be left behind in that race to place their solutions in data centers worldwide. The Crusoe company, which is dedicated to the construction of large AI data centers, advertisement A few days ago I would spend 400 million dollars in AMD’s chips, and even Sam Altman, CEO of OpenAi, made a surprise appearance During the inaugural talk of the Lisa Su, CEO of AMD event. Altman said they will also use AMD chips in the data centers they use, and highlighted that the new AMD ia gpus “will be somewhat amazing.” AMD presumes to be more efficient (and cheap). AMD’s message was clear during the event: its MI355 offer much more efficiency and are cheaper than NVIDIA B200 and GB200 with comparable yields. The sales prices of those GPUS are not known, but we do know that at the beginning of 2024 the MI300x of AMD They cost a maximum of $ 15,000 for the more than $ 40,000 that cost The NVIDIA H100. The biggest challenge is still CUDA. The benefits of AMD AI chips are not in fact the problem of this company. Detailed studies revealed months ago that MI300X are clearly higher than NVIDIA H100 and H200 on performance and power. However, Nvidia has a Cudathe de facto standard in the industry for services of services and applications of AI. Using AMD native software is feasible, yes, but software experience, They assured in SEMIANALYSIS“Software is full of errors that make training (AI models) with AMD it is impossible.” AMD’s hope is Rocm. In that AMD event also presented Rocm 7, the latest version from your own Open Source programming platform for your GPUS. In AMD they indicated that this version is 3.5 times more powerful than Rocm 6, and even claim that it is 30% more powerful than CUDA in the B200 when serving the model Deepseek R1. Even so, they indicate In another report of semi -health, it is still lower in some sections. Getting that component allows developers to take advantage of all the potential of AMD’s chips is precisely key to the future of those efforts. Even … Read more

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