Quobyte

Here is Jimmy's recap of GTC, and a quick piece of advice regarding AI workloads: #NIVIDIAGTCRecap #GPUConverged #Quobyte #AIInfrastructure

We had a great week at NVIDIA GTC, filled with great conversations! Thank you to everyone who stopped by our booth, talked to us about their AI projects, and shared their infrastructure challenges. Our GPU Converged storage solution was a hot topic; AI teams were delighted to hear that Quobyte is the only software storage solution that can run directly on GPU nodes, turning idle resources into a reliable, high-performance storage system. We hope to see you at our next show! #NVIDIAGTC #GTCRecap #GPUConverged #AIInfrastructure #Quobyte

The energy at GTC is amazing on day three! We've had great discussions and insightful conversations at booth #7003, and it's not over yet! We will be doing our second presentation at Oracle's booth, #1613, today at 2:55 PM. If you want to learn how to leverage the unused resources in the OCI GPU nodes you already paid for! You can also come directly to our booth, #7003, to get some cool swag, take a picture with Jimmy, and learn how he realized NFS is not suited for AI. #GTC2026 #AIInfrastructure #GPUConverged #Quobyte #OCI

Day 2 at GTC made one thing clear: AI teams are looking for smarter ways to do AI Infrastructure. We’ve had great conversations with leaders who want to grow AI capacity without adding more hardware, complexity, or overhead. That’s exactly why Quobyte GPU Converged is resonating. By turning the idle CPU and NVMe already inside existing GPU nodes into high-performance, ultra-reliable storage, organizations can take a more efficient approach to AI infrastructure growth. If you’re at GTC, stop by Booth #7003 and see how we’re helping teams rethink storage for modern AI environments. #GTC2026 #AIInfrastructure #GPUConverged #Quobyte

We had a great discussion at Oracle's booth about GPU Converged Storage! Our audience was excited to learn how to maximize ROI on GPU nodes. If you are at GTC and you missed it, don't worry! You will have another chance to catch us at Oracle's booth (#1613) tomorrow, Wednesday, March 18, at 2:55 PM. Don't miss this great opportunity to learn how to leverage unused resources on GPU nodes you already paid for. Hope to see you there. #GTC2026 #AIInfrastructure #OCI # Quobyte #ArchitectedForAI #GPUConverged

Did you know that your Oracle Cloud Infrastructure GPU nodes can also serve as a reliable, fast storage system with GPU Converged storage? Quobyte GPU Converge leverages the unused resources on OCI GPU nodes you've already paid for, turning them into a powerful storage system! We will be at Oracle's booth, #1613, demonstrating how easy it is to get started with GPU Converged. Date and times: Tuesday, March 17 at 12:15-12:45 PM Wednesday, March 18, at 2:55-3:25 PM Hope to see you there! #NVIDIAGTC2026 #OracleCloud #ArchitectedForAI #GPUConverged #Quobyte

NVIDIA GTC 2026 is underway, and we can't wait to show you a different way to do AI Storage! Swing by booth #7003 to learn how we turn idle resources like NVME and CPUs inside your GPU nodes into a reliable, high-performance storage system. Get 5x faster storage without storage appliances, less networking, and lower power consumption with Quobyte GPU Converged storage. Come to our booth to get some exclusive swag! #NVIDIAGTC2026 #AIInfrastructure #ArchitectedForAI #Quobyte

GTC is almost here, and if AI infrastructure efficiency is on your 2026 priority list, make time to stop by Booth #7003. Most storage vendors still ask you to solve AI growth with more boxes, more power, more ports, and more budget. We think there’s a better way. Quobyte GPU Converged turns the idle CPU and NVMe already inside your GPU nodes into ultra-reliable, high-performance storage, so you can scale AI without scaling storage sprawl. The result: faster storage with 5x less power and zero new hardware. That means less infrastructure to deploy, fewer networking resources to consume, and a much more efficient path to growing your AI environment. We would love to talk to you about architecture, performance, and operational simplicity. If you’re focused on budgets and ROI, let’s talk about how to reduce storage costs, power draw, and infrastructure overhead without slowing the business down. Visit us at NVIDIA GTC Booth #7003 to see how AI storage can be done differently. #NVIDIAGTC2026 #AIInfrastructure #GPUConverged #Quobyte

Thrilled to welcome Andrew Perry as Vice President of Sales at Quobyte. With 20+ years of enterprise storage expertise, Andrew has built world-class sales organizations and scaled high-performance teams through major industry shifts. Read the full announcement: quobyte.com/quobyte-appoin…

Most AI clusters still add separate storage appliances, more racks, more switches, more power. At NVIDIA GTC next week, we’re showing a different approach. With Quobyte GPU Converged Storage, the storage layer runs directly on your GPU nodes, turning the idle CPU and NVMe already inside your cluster into a shared, high-performance storage system. No extra appliances, no new racks, and no storage lead times. Just massively parallel storage that scales with your GPU fleet. The economics are hard to ignore: • Up to 78% lower storage TCO • Up to 89% lower power consumption If you're heading to GTC, come see it in action at Booth #7003. #NVIDIAGTC26 #AIInfrastructure #GPUConverged #Quobyte

Two weeks from now in San Jose, you’ll see AI storage done a completely different way: no new hardware, just smarter software. We’ll be at the Nvidia GTC Booth #7003, showing how we turn the idle CPU and NVMe inside your existing GPU nodes into ultra-reliable, high-performance storage, so you can skip lead times and hardware tax. Highlights: *Zero lead time: install on your existing GPU nodes *Performance that scales in lockstep with every new GPU *Up to 78% lower TCO by using the hardware already inside your GPU nodes Heading to the show? Swing by Booth #7003 or drop a comment, and let’s talk about making your AI infrastructure faster without buying another box. #GTC2026 #AIInfrastructure #GPUConverged #AIStorage

Are you heading to Nvidia GTC 2026? Stop by booth 7003 and let’s talk about GPU converged and how it can help you get more of the hardware you already own. GPU Converged lets you turn the underused CPU cores and local NVMe inside your GPU nodes into a high‑performance, resilient storage platform for training and inference. You keep the same GPU fleet, but now those “idle” resources work for you instead of just sitting there, lowering power and infrastructure spend. Swing by our booth at GTC to see how storage that runs directly on GPU nodes scales as you add GPUs, eliminate external storage bottlenecks, and help you maximize your ROI out of every GPU node in your AI cluster. Learn more about GPU Converged: buff.ly/WatbUYF #NvidiaGTC26 #GTC26 #GPU #AI #GPUConverged

We’re excited to be heading to NVIDIA GTC in San Jose this March! It’s the place to be for AI innovation, but let’s be real: if you’re still buying dedicated storage appliances for your GPU clusters, you’re missing the point - and lighting money on fire. Stop by Booth 7003 to see the math for yourself. We’ll be running live reports with our Quobyte GPU Converged Savings Calculator to show you exactly how much rack space, power, and capital you’re burning by sticking with legacy architecture. Stop the burn. See you at Booth 7003! Learn more about our calculator here: buff.ly/2GSH5rM #GTC26 #AIInfrastructure #Quobyte #GPU

Quobyte GPU Converged storage delivers 78% lower storage TCO and 87% lower power consumption. Yes, we double-checked. So should you, calculate your savings in under a minute: quobyte.com/gpu-converged-…

In many AI environments, storage appliances limit performance, increase power consumption, and drive up cost while expensive GPUs sit underutilized. @Quobyte GPU Converged Storage removes the appliance entirely by running storage directly on GPU nodes and using existing CPUs and NVMe. As GPU nodes scale, storage performance scales with them. The result is up to 78% lower TCO and 87% lower power consumption compared to traditional appliance-based architectures. See what this means for your cluster with the GPU Converged Savings Calculator: quobyte.com/gpu-converged-…

Idle CPUs in GPU fleets still draw power and drive infrastructure costs, often totaling $250M/year across ~10,000 nodes. Most teams don’t quantify that cost. So we built a calculator that does. Input your fleet size, get your 3-year TCO across: Power consumption Switch ports required Rack space Hardware + software costs In ~90 seconds, see your 3-year TCO across power consumption, rack space, switch ports, and storage costs. Calculate yours: buff.ly/w8sAquy #AIInfrastructure #DataCenter #AI #GPU

The most expensive part of your AI infrastructure might be doing... nothing. In a fleet of 10,000 GPU nodes, idle CPUs can burn through over $250 million in electricity per year without contributing to your workload. But here's the real problem: to handle storage, you're adding more infrastructure. New appliances, switches, and cabling. In addition to more racks, complexity, and failure points. Quobyte GPU Converged changes that: no new wiring, appliances, or demand for scarce switch ports. Quobyte turns your GPU nodes into a resilient, bulletproof storage tier, turning wasted capacity into a unified, efficient platform that grows with your fleet. Stop adding more boxes to your data center and start using what you already have. See how it works: buff.ly/qBbpjj4 #Quobyte #GPUConverged #ArchitectedForAI #AIStorage

Why settle for slow, complex storage when AI needs both speed and simplicity? @Chris_Mellor at Blocks and Files just published a great deep dive into Quobyte’s quiet performance and scale advantage. He explains how Quobyte combines the “simple and reliable” strengths of enterprise storage with the “fast and scalable” power of HPC, without the usual complexity tax.​ Quobyte is architected for AI, bringing hyperscaler-style, software-only storage to this middle ground: resilient at datacenter scale, linearly scalable to feed GPUs, and simple enough that small teams can run petabyte-to-exabyte environments on standard hardware.​ Read his analysis here: bit.ly/3LsCEUG #Quobyte #ArchitectedForAI #AIStorage #AIInfrastructure #HPC #Hyperscaler #BlocksAndFiles

Running sensitive workloads, like genome data, medical records, or PII, on the same cluster as everyday projects is possible and secure with Quobyte High-Security Tenants. With Quobyte, you get a single storage platform with clearly separated, locked-down environments for high-sensitivity data, so you cut down on siloed infrastructure while keeping strong security and compliance controls. Key capabilities: *Enforced TLS and certificate-based access *Tenant-managed encryption keys *Optional hardware-level isolation for stricter environments High-security and regular tenants can share a single cluster securely. Learn more in our blog: buff.ly/XZzhwNN #Quobyte #ArchitectedForAI #DataSecurity #MultiTenancy #AIInfrastructure #HPC #StorageArchitecture