Nvidia unveils 88-core Vera CPU to challenge Intel and AMD in AI-driven data center market

Nvidia unveils details of new 88-core Vera CPUs positioned to compete with AMD and Intel - new Vera CPU rack features 256 liquid-cooled chips that deliver up to a 6X gain in CPU throughput

Nvidia announced more details about its new 88-core Vera data center CPUs at GTC 2026 here in San Jose, California, claiming impressive 50% performance gains over standard CPUs, fueled by a 1.5X increase in IPC from its Olympus cores and an innovative high-bandwidth design that Nvidia says delivers the fastest single-threaded performance on the market. The company also unveiled its new Vera CPU Rack architecture, which brings 256 liquid-cooled CPUs into one rack for CPU-centric workloads, claiming a 6X gain in CPU throughput and twice the performance in agentic AI workloads. The evolution of the Vera CPU and its integration into deployable rack-scale systems marks Nvidia's entry into direct CPU sales, positioning itself as a competitor to Intel and AMD in the traditional CPU market. That's not to mention competing against the many flavors of custom Arm processors used by the world's largest hyperscalers. This doesn't come as a complete surprise, coming in the wake of the company's announcement that Meta will now deploy multiple generations of Nvidia CPU-only systems across its infrastructure. Nvidia will also continue to use the CPUs for its own GPU-focused systems, such as the Vera Rubin platform we covered more in depth here. Nvidia originally introduced its first-gen Grace CPUs at GTC in 2022, foreshadowing that its continued evolution of the series would eventually position it to compete with the broader CPU market. The new processors target both AI-centric and more general-purpose use-cases, with a heavy emphasis on the former, and Nvidia's broadening of both the capabilities and its target markets will provide stiff competition for AMD and Intel as they battle for sockets in AI data centers. The chips are now in full production and will be available to Nvidia's partners in the second half of this year. Let's take a closer look at the new chips, and then the rack-scale architecture. Nvidia Vera CPU specifications and performance Nvidia designed the Vera CPU to provide the best of many worlds, with the intention of melding the high core counts of hyperscale cloud CPUs with the high single-thread performance of gaming CPUs and the power efficiency of mobile chips, all with the goal of speeding common GPU-driven tasks in agentic AI, training, and inference workloads, such as Python execution, SQL queries, and code compilation. All told, Nvidia claims 1.5x the performance-per-sandbox over x86 competitors, 3x the memory bandwidth per core, and twice the efficiency. To meet those goals, the company designed an 88-core CPU with 144 threads, an increase over the first-gen Grace's 72 cores. Nvidia also claims the cores offer a 1.5X improvement in instructions per cycle (IPC) throughput, a massive generational jump relative to other competing architectures, which tend to gain a single-digit or a low-teens percentage increase with each generation. With the previous-gen Grace, Nvidia used off-the-shelf Arm Neoverse cores, but the firm does stipulate that the new Olympus cores found on Vera are 'Nvidia designed,' signaling that the company has made custom modifications to the reference design. The Arm v9.2-A Olympus cores feature spatial multi-threading, which physically isolates the various components of the pipeline by not time-slicing the key elements, like the execution units, caches and register files, with the other thread running on the same core. This contrasts with the standard time-slicing found in other simultaneous multi-threading (SMT) implementations, a process that has the threads take turns utilizing the resources. Spatial Multi-Threading increases Instruction Level Parallelism (ILP), throughput, and performance predictability by pulling instructions from other threads when execution elements are idle, thus ensuring full utilization. In effect, this allows both threads to truly run simultaneously on a single core, whereas in a standard SMT implementation the threads essentially take turns running on a single core. Naturally, this will be a boon for multi-tenancy environments. Nvidia arranges all 88 cores in a single domain, so there are no latency-inducing NUMA eccentricities to be found, in stark contrast to current high core-count x86 competitors. This has dramatic implications for latency, predictability, bandwidth, and ease-of-programmability. The firm has not shared the full details of how it accomplished this feat while maintaining adequate latency to each core, but the chip features a new generation of the Nvidia Scalable Coherency Fabric (SCF), a mesh topology built from Arm's CMN-700 Coherent Mesh Network used in Grace's Arm Neoverse cores. Arm has moved forward to the newer Neoverse CMN S3 mesh with its latest designs, and Vera likely employs that design, or a variant thereof. The mesh network can deliver impressive memory throughput to the cores in aggregate, and even more when certain cores are more bandwidth-hungry than others. Grace supported 546 GB/s of memory throughput to the mesh, working out to an average of 7.6 GB/s per core. Vera more than doubles that to 1.2 TB/s of bandwidth fed by 1.5TB of SOCAMM LPPDDR5 modules (a 3x increase in capacity), which works out to an average of 13.6 GB/s per core in full-load conditions. Importantly, the architecture now supports up to 80 GB/s of throughput to any single core when load conditions aren't consistent across the mesh, an impressive uplift for bandwidth-hungry threads. The execution pathway includes a 10-wide Instruction Decode unit, a neural branch predictor that supports two branch predictions per cycle, a custom graph database analytics prefetch engine, and a PyTorch-optimized Instruction Buffer. The chip fully supports Confidential Computing, a notable advance over Grace that allows for fully protected CPU+GPU domains. The CPU also features an NVLink-C2C die-to-die interface with up to 1.8 TB/s of throughput, a doubling of Grace's 900 GB/s interconnect and seven times faster than PCIe 6.0. It also supports two-processor (2P) configurations. Overall, Vera supports the full suite of technologies expected from a modern data center processor, including PCIe 6.0 and CXL 3.1 support, but with a bandwidth and latency-focused compute design that positions its uniquely well for use in AI workflows. The Vera CPU Rack and Benchmark Performance Grace has already served as a fundamental building block in many Nvidia GPU+CPU systems, including some of the fastest AI supercomputers on the planet, but Nvidia's expanded goal is to leverage Vera in pure-play CPU racks that can be more widely deployed. The Vera CPU rack meets that goal with 256 liquid-cooled Vera CPUs paired with 74 Bluefield-4 DPUs and ConnectX SuperNIC networking. The rack weighs in with up to 400 TB of LPDDR5 and 300 TB/s of aggregate memory throughput. That feeds the 45,056 threads, which Nvidia says supports 22,500 concurrent CPU environments running independently. Nvidia shared benchmarks in a wide range of workloads, touting from a 1.8x to 2.2x performance improvement over Grace in scripting, compilation, data analytics, graph analytics, and HPC workloads, among others. Naturally one would expect this system to be deployed at Meta, which recently announced its partnership with Nvidia for CPU-only systems, but Nvidia says it will also offer the Vera CPU rack system to hyperscalers, including Oracle, Coreweave, Nebius, Alibaba, and others. A broad range of OEMs and ODMs will also provide single- and dual-socket servers for the broader market for a wide range of use cases, including industry heavyweights like Dell, HPE, Lenovo, Supermicro, Foxconn, and many others. The Vera CPUs will also be used for Nvidia HGX NVL8 systems. Perhaps most importantly, these racks will also serve as an integral part of Nvidia's broader Vera Rubin platform, which features seven chips in total, including the Rubin GPU, NVLink6 Switch for rack-scale interconnect, ConnectX-9 SuperNIC for networking, Bluefield 4 DPU, Spectrum-X 102.4T Co-packaged Optics switch, and Nvidia's Groq 3 LPUs. The Vera CPUs are in full production now and are slated for deliveries beginning in the second half of this year. Follow Tom's Hardware on Google News, or add us as a preferred source, to get our latest news, analysis, & reviews in your feeds.

Nvidia crams 256 Vera CPUs into a single liquid cooled rack

GTC Intel and AMD take notice. At GTC on Monday, Nvidia unveiled its latest liquid-cooled rack systems. But unlike its NVL72 racks, this one isn't powered by GPUs or even Groq LPUs, but rather 256 of its custom Vera CPUs. The system is designed to support AI training techniques like reinforcement learning as well as agentic AI frameworks and services that can't run on GPUs alone. "Agents don't operate on GPUs alone. They need CPUs in order to do their work, whether we're training agentic models or serving them, GPUs today actually call out to CPUs in order to do the tool calling, SQL queries and the compilation of code," Ian Buck, VP of Hyperscale and HPC at Nvidia told press on Sunday. "This sandbox execution is a critical part of both training and deploying agents across data centers." Those CPUs need to be fast to avoid becoming a bottleneck. That requires a new kind of AI-optimized CPU which balances per core frequency, density, and power efficiency, Buck argues. Nvidia is no stranger to CPU design. Its first datacenter CPU, Grace, was announced nearly five years ago and has become an integral part of the company's Grace-Hopper and Grace-Blackwell rack systems since. While most of these deployments were tied to GPU systems or HPC clusters, Meta recently revealed plans to deploy Nvidia's standalone Grace CPUs at scale within its datacenters. Vera is Nvidia's latest CPU and brings several notable improvements, including 88 custom Olympus Arm cores, support for simultaneous multithreading, a much wider memory bus, and faster chip-to-chip interconnects. In addition to powering Nvidia's Vera-Rubin superchips, paper-launched at CES earlier this year, Nvidia plans to offer its CPUs as an alternative to x86 chips from Intel and AMD. The company is making some rather bold claims about its latest CPU superchips. If Nvidia is to be believed, Vera will deliver 3x more memory bandwidth and 1.5x the performance per core than contemporary x86 processors. Much of that performance is down to Nvidia's new Olympus Arm cores, which now feature a 10-wide decode pipeline with what Nvidia describes as a "neural branch predictor" that can perform two branch predictions per cycle. Branch prediction is key to performance in modern CPUs, and involves anticipating future code paths and executing down them before they're needed. By predicting two paths per cycle, Vera decreases the likelihood of a miss predict, theoretically boosting its performance in the process. Nvidia also benefits from its use of LPDDR5X memory, more commonly found in notebook computers, rather than the RDIMMS used by conventional servers. Each Vera CPU can be equipped with up to 1.5 TB of LPDDR5 SOCAMM memory modules good for 1.2 TB/s of bandwidth per socket. For reference, Intel's top 6900P processors top out at 825 GB/s of bandwidth when using 8800 MT/s MRDIMMs, while AMD's Turin processors top out between 560 and 600 GB/s. The chips also feature faster NVLink-C2C interconnects, enabling them to shuffle data to and from other CPU or GPUs at up to 900 GB/s (advertised as 1.8 TB/s bidirectional bandwidth) in either direction. Many of the tasks performed by agentic systems involve retrieving data and executing code against it, making high memory bandwidth key to avoiding bottlenecks. Vera will be available in both single- and dual-socket configurations from the usual ODM and OEM suspects, including Foxconn, Wistron, Dell Tech, Lenovo, and HPE, to name a handful. That means that this time around Nvidia will actually be competing head-to-head with AMD and Intel in the CPU space. To this end, Nvidia says that its NVL8 HGX systems, which have traditionally used x86 processors from Intel, will be offered with Vera CPUs for the Rubin generation. For high-density deployments, Nvidia also has a new MGX reference design that packs up to 256 Vera processors along with 64 BlueField-4 data processing units into a single liquid-cooled rack, providing more than 22,500 CPU cores, and 400 TB of memory for agents to retrieve data and execute code. It doesn't look like Nvidia will need to fight to win over customers. When Vera makes its debut later this year, Alibaba, ByteDance, Meta, Oracle, CoreWeave, Lambda, Nebius, and NScale have all committed to deploying the chips in their datacenters. ®

Nvidia unveils AI infrastructure spanning chips to space computing

The company says the new processor and rack-scale architecture are built to handle the rapid growth of AI workloads, where software agents increasingly plan tasks, execute code and interact with other systems autonomously. The Vera CPU is designed specifically for these emerging workloads. According to Nvidia, the processor delivers results with twice the efficiency and is 50 percent faster than traditional rack-scale CPUs. The chip is expected to power AI data centers used for training models, running AI agents and managing massive computing clusters across cloud platforms and enterprise systems. Nvidia says the Vera CPU marks a shift in how processors support modern AI systems. Rather than simply supporting GPUs, CPUs are becoming central to coordinating AI workloads across large computing environments. "Vera is arriving at a turning point for AI. As intelligence becomes agentic -- capable of reasoning and acting -- the importance of the systems orchestrating that work is elevated," said Jensen Huang, founder and CEO of Nvidia. "The CPU is no longer simply supporting the model; it's driving it. With breakthrough performance and energy efficiency, Vera unlocks AI systems that think faster and scale further."

NVIDIA Launches Vera CPU, Purpose-Built for Agentic AI

GTC -- NVIDIA today launched the NVIDIA Vera CPU, the world's first processor purpose-built for the age of agentic AI and reinforcement learning -- delivering results with twice the efficiency and 50% faster than traditional rack-scale CPUs. As reasoning and agentic AI advances, scale, performance and cost are increasingly driven by the infrastructure supporting the models that plan tasks, run tools, interact with data, run code and validate results. The NVIDIA Vera CPU builds on the success of the NVIDIA Grace™ CPU, enabling organizations of all sizes and across industries to build AI factories that unlock agentic AI at scale. With the highest single-thread performance and bandwidth per core, Vera is a new class of CPU that delivers higher AI throughput, responsiveness and efficiency for large-scale AI services such as coding assistants, as well as consumer and enterprise agents. Leading hyperscalers collaborating with NVIDIA to deploy Vera include Alibaba, CoreWeave, Meta and Oracle Cloud Infrastructure, as well as global system makers Dell Technologies, HPE, Lenovo, Supermicro and others. This broad adoption establishes Vera as the new CPU standard for the AI workloads that matter most for developers, startups, public-private institutions and enterprises -- helping democratize access to AI and accelerating innovation. "Vera is arriving at a turning point for AI. As intelligence becomes agentic -- capable of reasoning and acting -- the importance of the systems orchestrating that work is elevated," said Jensen Huang, founder and CEO of NVIDIA. "The CPU is no longer simply supporting the model; it's driving it. With breakthrough performance and energy efficiency, Vera unlocks AI systems that think faster and scale further." Configurable for Every Data Center NVIDIA announced a new Vera CPU rack integrating 256 liquid-cooled Vera CPUs to sustain more than 22,500 concurrent CPU environments, each running independently at full performance. AI factories can quickly deploy and scale to tens of thousands of simultaneous instances and agentic tools in a single rack. The new Vera rack is built using the NVIDIA MGX™ modular reference architecture, supported by 80 ecosystem partners worldwide. As part of the NVIDIA Vera Rubin NVL72 platform, Vera CPUs are paired with NVIDIA GPUs through NVIDIA NVLink™-C2C interconnect technology, with 1.8 TB/s of coherent bandwidth -- 7x the bandwidth of PCIe Gen 6 -- for high-speed data sharing between CPUs and GPUs. Additionally, NVIDIA introduced new reference designs that use Vera as the host CPU for NVIDIA HGX™ Rubin NVL8 systems, coordinating data movement and system control for GPU-accelerated workloads. Vera systems partners are providing both dual and single-socket CPU server configurations, optimal for workloads such as reinforcement learning, agentic inference, data processing, orchestration, storage management, cloud applications and high-performance computing. Across all configurations, Vera systems integrate NVIDIA ConnectX SuperNIC cards and NVIDIA BlueField-4 DPUs for accelerated networking, storage and security, which are critical for agentic AI. This enables customers to optimize for their specific workloads while maintaining a single software stack across the NVIDIA platform. Designed for Agentic Scaling By combining high-performance, energy-efficient CPU cores, a high-bandwidth memory subsystem and the second-generation NVIDIA Scalable Coherency Fabric, Vera enables faster agentic responses under the extreme utilization conditions common for agentic AI and reinforcement learning. Vera features 88 custom NVIDIA-designed Olympus cores, delivering high performance for compilers, runtime engines, analytics pipelines, agentic tooling and orchestration services. Each core can run two tasks, using NVIDIA Spatial Multithreading, to deliver consistent, predictable performance -- ideal for multi-tenant AI factories running many jobs at once. To further enhance energy efficiency, Vera introduces the second generation of NVIDIA's low-power memory subsystem, now built on LPDDR5X memory and delivering up to 1.2 TB/s of bandwidth -- twice the bandwidth and at half the power compared with general-purpose CPUs. Widespread Ecosystem Support Cursor, an innovator in AI-native software development, is adopting NVIDIA Vera to boost performance for its AI coding agents. "We're excited to use NVIDIA Vera CPUs to improve overall throughput and efficiency so we can deliver faster, more responsive coding agent experiences for our customers," said Michael Truell, cofounder and CEO of Cursor. Redpanda, a leading streaming data and AI platform, is using Vera to dramatically boost performance. "Redpanda recently tested NVIDIA Vera running Apache Kafka-compatible workloads and saw dramatically better performance than other systems we've benchmarked, delivering up to 5.5x lower latency," said Alex Gallego, founder and CEO of Redpanda. "Vera represents a new direction in CPU architecture, with more memory and less overhead per core, enabling our customers to scale real-time streaming workloads further than ever and unlock new AI and agentic applications." National laboratories planning to deploy Vera CPUs include Leibniz Supercomputing Centre, Los Alamos National Laboratory, Lawrence Berkeley National Laboratory's National Energy Research Scientific Computing Center and the Texas Advanced Computing Center (TACC). "At TACC, we recently tested NVIDIA's Vera CPU platform as we prepare for deployment in our upcoming Horizon system -- and running six of our scientific applications, we saw impressive early results," said John Cazes, director of high-performance computing at TACC. "Vera's per-core performance and memory bandwidth represent a giant step forward for scientific computing, and we look forward to bringing Vera-based nodes to our CPU users on Horizon later this year." Leading cloud service providers planning to deploy Vera CPUs include Alibaba, ByteDance, Cloudflare, CoreWeave, Crusoe, Lambda, Nebius, Nscale, Oracle Cloud Infrastructure, Together.AI and Vultr. Leading infrastructure providers adopting Vera CPUs include Aivres, ASRock Rack, ASUS, Compal, Cisco, Dell, Foxconn, GIGABYTE, HPE, Hyve, Inventec, Lenovo, MiTAC, MSI, Pegatron, Quanta Cloud Technology (QCT), Supermicro, Wistron and Wiwynn. Availability NVIDIA Vera is in full production and will be available from partners in the second half of this year.

Nvidia reinvents the CPU for the age of agentic AI - SiliconANGLE

For a while, it was thought that generic central processing units had little role to play in the artificial intelligence revolution, but Nvidia Corp. begs to differ. At its GTC 2026 developer conference today, it announced the all-new Vera CPU, said to be the first chip of its kind designed specifically for agentic AI workloads and reinforcement learning. As AI evolves from simple chatbots towards autonomous AI agents that can reason, use third-party software tools, write and execute code on behalf of humans, the underlying infrastructure requirements are changing. According to Nvidia, AI agents need more than just the sheer power and performance of graphics processing units. They also require orchestration, data movement and validation logic, which are tasks best performed by traditional CPUs. That's why Nvidia developed the Vera CPU, which it says is 50% faster and twice as efficient as traditional x86-based CPUs when handling these complex operations. "Vera is arriving at a turning point for AI," said Nvidia Chief Executive Jensen Huang. "The CPU is no longer simply supporting the model; it's driving it. With breakthrough performance and energy efficiency, Vera unlocks AI systems that think faster and scale further." Vera is the successor to Nvidia's Grace CPU, and it has been designed to slot inside the vast "AI factories" that power today's most powerful large language models. The new chip features 88 custom-designed Olympus cores that utilize Nvidia's Spatial Multithreading technology to run two tasks simultaneously with more predictable performance than its predecessor. That's a must-have for cloud infrastructure providers that need to run thousands of AI agents at once. To feed these cores, Nvidia has equipped the Vera CPUs with a new low-power memory subsystem that uses LPDDR5X memory. It delivers a massive 1.2 terabytes-per-second of bandwidth, which is about twice that of the general-purpose CPUs, while using only half the amount of power. Nvidia said the Vera chips excel at AI "thinking" tasks. By that, it's referring to the compilers, analytics pipelines and orchestration services that tell GPUs what they should be doing next. The GPUs remain the workhorse of AI models, while the CPUs perform the management tasks. Early adopters have already reported substantial performance gains, with Vera delivering 5.5 times lower latency when running Apache Kafka workloads, according to the data streaming company Redpanda Data Inc. Nvidia isn't just selling bags of the new chips. It's also offering a new Vera CPU rack system that integrates 256 liquid-cooled chips together to tackle the biggest AI workloads. According to Nvidia, it's able to sustain more than 22,500 concurrent CPU environments, which means AI factories will be able to scale agentic services to tens of thousands of instances within a remarkably small physical footprint. The Vera CPUs are also integrated in Nvidia's new NVL72 platform, which is a liquid-cooled rack-scale system made up of 72 Rubin GPUs and 36 Vera CPUs connected over its high-speed NVLink 6 interconnects. The company said it's able to provide up to 1.8 TB-per-second of coherent bandwidth between the CPU and GPUs, which is about seven times more than the latest PCIe Gen 6 standard. It's fast enough that Nvidia promises the CPU will no longer be a bottleneck that causes GPUs to sit idle, waiting for data to perform training and inference tasks. Nvidia is betting on broad industry adoption of the Vera CPU platform, and it has an extensive list of partners at launch. Hyperscale data center operators including Oracle Corp., Meta Platforms Inc. and Alibaba Group Holding Ltd. will be among the first to deploy the Vera CPU rack-scale systems, together with "neocloud" platforms such as CoreWeave Inc. and Nebius Group NV. Meanwhile, Nvidia has a long list of hardware providers backing it too. These include Dell Technologies Inc., Hewlett Packard Enterprise Co., Supermicro Computer Inc. and Lenovo Group Ltd., which are all planning to launch Vera CPU-based servers in the coming months. These will range from specialized HGX Rubin systems for GPU-accelerated AI workloads, to dual-socket configurations for general data processing. Nvidia said the Vera CPUs are in full production now, with the first Vera-based systems set to come available in the second half of the year.