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Generative AI has reshaped how people create, imagine and interact with digital content. As AI models continue to grow in capability and complexity, they require more VRAM, or video random access memory. The base Stable Diffusion 3.5 Large model, for example, uses over 18GB of VRAM — limiting the number of systems that can run it well. By applying quantization to the model, noncritical layers can be removed or run with lower precision. NVIDIA GeForce RTX 40 Series and the Ada Lovelace generation of NVIDIA RTX PRO GPUs support FP8 quantization to help run these quantized models, and the latest-generation NVIDIA Blackwell GPUs also add support for FP4. NVIDIA collaborated with Stability AI to quantize its latest model, Stable Diffusion (SD) 3.5 Large, to FP8 — reducing VRAM consumption by 40%. Further optimizations to SD3.5 Large and Medium with the NVIDIA TensorRT software development kit (SDK) double performance. In addition, TensorRT has been reimagined for RTX AI PCs, combining its industry-leading performance with just-in-time (JIT), on-device engine building and an 8x smaller package size for seamless AI deployment to more than 100 million RTX AI PCs. TensorRT for RTX is now available as a standalone SDK for developers. RTX-Accelerated AI NVIDIA and Stability AI are boosting the performance and reducing the VRAM requirements of Stable Diffusion 3.5, one of the world’s most popular AI image models. With NVIDIA TensorRT acceleration and quantization, users can now generate and edit images faster and more efficiently on NVIDIA RTX GPUs. Stable Diffusion 3.5 quantized FP8 (right) generates images in half the time with similar quality as FP16 (left). Prompt: A serene mountain lake at sunrise, crystal clear water reflecting snow-capped peaks, lush pine trees along the shore, soft morning mist, photorealistic, vibrant colors, high resolution. To address the VRAM limitations of SD3.5 Large, the model was quantized with TensorRT to FP8, reducing the VRAM requirement by 40% to 11GB. This means five GeForce RTX 50 Series GPUs can run the model from memory instead of just one. SD3.5 Large and Medium models were also optimized with TensorRT, an AI backend for taking full advantage of Tensor Cores. TensorRT optimizes a model’s weights and graph — the instructions on how to run a model — specifically for RTX GPUs. FP8 TensorRT boosts SD3.5 Large performance by 2.3x vs. BF16 PyTorch, with 40% less memory use. For SD3.5 Medium, BF16 TensorRT delivers a 1.7x speedup. Combined, FP8 TensorRT delivers a 2.3x performance boost on SD3.5 Large compared with running the original models in BF16 PyTorch, while using 40% less memory. And in SD3.5 Medium, BF16 TensorRT provides a 1.7x performance increase compared with BF16 PyTorch. The optimized models are now available on Stability AI’s Hugging Face page. NVIDIA and Stability AI are also collaborating to release SD3.5 as an NVIDIA NIM microservice, making it easier for creators and developers to access and deploy the model for a wide range of applications. The NIM microservice is expected to be released in July. TensorRT for RTX SDK Released Announced at Microsoft Build — and already available as part of the new Windows ML framework in preview — TensorRT for RTX is now available as a standalone SDK for developers. Previously, developers needed to pre-generate and package TensorRT engines for each class of GPU — a process that would yield GPU-specific optimizations but required significant time. With the new version of TensorRT, developers can create a generic TensorRT engine that’s optimized on device in seconds. This JIT compilation approach can be done in the background during installation or when they first use the feature. The easy-to-integrate SDK is now 8x smaller and can be invoked through Windows ML — Microsoft’s new AI inference backend in Windows. Developers can download the new standalone SDK from the NVIDIA Developer page or test it in the Windows ML preview. For more details, read this NVIDIA technical blog and this Microsoft Build recap. Join NVIDIA at GTC Paris At NVIDIA GTC Paris at VivaTech — Europe’s biggest startup and tech event — NVIDIA founder and CEO Jensen Huang yesterday delivered a keynote address on the latest breakthroughs in cloud AI infrastructure, agentic AI and physical AI. Watch a replay. GTC Paris runs through Thursday, June 12, with hands-on demos and sessions led by industry leaders. Whether attending in person or joining online, there’s still plenty to explore at the event. Each week, the RTX AI Garage blog series features community-driven AI innovations and content for those looking to learn more about NVIDIA NIM microservices and AI Blueprints, as well as building AI agents, creative workflows, digital humans, productivity apps and more on AI PCs and workstations.  Plug in to NVIDIA AI PC on Facebook, Instagram, TikTok and X — and stay informed by subscribing to the RTX AI PC newsletter. Follow NVIDIA Workstation on LinkedIn and X.  See notice regarding software product information.

Google and OpenAI struck a cloud computing deal in May, according to a Reuters report. The deal surprised the industry as the two are seen as major AI rivals. Signs of friction between OpenAI and Microsoft may have also fueled the move. The partnership is a win-win.OpenAI gets more badly needed computing resources while Google profits from its $75B investment to boost its cloud computing capacity in 2025. In a surprise move, Google and OpenAI inked a deal that will see the AI rivals partnering to address OpenAI’s growing cloud computing needs. The story, reported by Reuters, cited anonymous sources saying that the deal had been discussed for months and finalized in May. Around this time, OpenAI has struggled to keep up with demand as its number of weekly active users and business users grew in Q1 2025. There’s also speculation of friction between OpenAI and its biggest investor Microsoft. Why the Deal Surprised the Tech Industry The rivalry between the two companies hardly needs an introduction. When OpenAI’s ChatGPT launched in November 2022, it posed a huge threat to Google that triggered a code red within the search giant and cloud services provider. Since then, Google has launched Bard (now known as Gemini) to compete with OpenAI head-on. However, it had to play catch up with OpenAI’s more advanced ChatGPT AI chatbot. This led to numerous issues with Bard, with critics referring to it as a half-baked product. A post on X in February 2023 showed the Bard AI chatbot erroneously stating that the James Webb Telescope took the first picture of an exoplanet. It was, in fact, the European Southern Observatory’s Very Large Telescope that did this in 2004. Google’s parent company Alphabet lost $100B off its market value within 24 hours as a result. Two years on, Gemini made significant strides in terms of accuracy, quoting sources, and depth of information, but is still prone to hallucinations from time to time. You can see examples of these posted on social media, like telling a user to make spicy spaghetti with gasoline or the AI thinking it’s still 2024.  And then there’s this gem: With the entire industry shifting towards more AI integrations, Google went ahead and integrated its AI suite into Search via AI Overviews. It then doubled down on this integration with AI Mode, an experimental feature that lets you perform AI-powered searches by typing in a question, uploading a photo, or using your voice. In the future, AI Mode from Google Search could be a viable competitor to ChatGPT—unless of course, Google decides to bin it along with many of its previous products. Given the scope of the investment, and Gemini’s significant improvement, we doubt AI + Search will be axed. It’s a Win-Win for Google and OpenAI—Not So Much for Microsoft? In the business world, money and the desire for expansion can break even the biggest rivalries. And the one between the two tech giants isn’t an exception. Partly, it could be attributed to OpenAI’s relationship with Microsoft. Although the Redmond, Washington-based company has invested billions in OpenAI and has the resources to meet the latter’s cloud computing needs, their partnership hasn’t always been rosy.  Some would say it began when OpenAI CEO Sam Altman was briefly ousted in November 2023, which put a strain on the ‘best bromance in tech’ between him and Microsoft CEO Satya Nadella. Then last year, Microsoft added OpenAI to its list of competitors in the AI space before eventually losing its status as OpenAI’s exclusive cloud provider in January 2025. If that wasn’t enough, there’s also the matter of the two companies’ goal of achieving artificial general intelligence (AGI). Defined as when OpenAI develops AI systems that generate $100B in profits, reaching AGI means Microsoft will lose access to the former’s technology. With the company behind ChatGPT expecting to triple its 2025 revenue to $12.7 from $3.7B the previous year, this could happen sooner rather than later. While OpenAI already has deals with Microsoft, Oracle, and CoreWeave to provide it with cloud services and access to infrastructure, it needs more and soon as the company has seen massive growth in the past few months. In February, OpenAI announced that it had over 400M weekly active users, up from 300M in December 2024. Meanwhile, the number of its business users who use ChatGPT Enterprise, ChatGPT Team, and ChatGPT Edu products also jumped from 2M in February to 3M in March. The good news is Google is more than ready to deliver. Its parent company has earmarked $75B towards its investments in AI this year, which includes boosting its cloud computing capacity. In April, Google launched its 7th generation tensor processing unit (TPU) called Ironwood, which has been designed specifically for inference. According to the company, the new TPU will help power AI models that will ‘proactively retrieve and generate data to collaboratively deliver insights and answers, not just data.’The deal with OpenAI can be seen as a vote of confidence in Google’s cloud computing capability that competes with the likes of Microsoft Azure and Amazon Web Services. It also expands Google’s vast client list that includes tech, gaming, entertainment, and retail companies, as well as organizations in the public sector. As technology continues to evolve—from the return of 'dumbphones' to faster and sleeker computers—seasoned tech journalist, Cedric Solidon, continues to dedicate himself to writing stories that inform, empower, and connect with readers across all levels of digital literacy. With 20 years of professional writing experience, this University of the Philippines Journalism graduate has carved out a niche as a trusted voice in tech media. Whether he's breaking down the latest advancements in cybersecurity or explaining how silicon-carbon batteries can extend your phone’s battery life, his writing remains rooted in clarity, curiosity, and utility. Long before he was writing for Techreport, HP, Citrix, SAP, Globe Telecom, CyberGhost VPN, and ExpressVPN, Cedric's love for technology began at home courtesy of a Nintendo Family Computer and a stack of tech magazines. Growing up, his days were often filled with sessions of Contra, Bomberman, Red Alert 2, and the criminally underrated Crusader: No Regret. But gaming wasn't his only gateway to tech.  He devoured every T3, PCMag, and PC Gamer issue he could get his hands on, often reading them cover to cover. It wasn’t long before he explored the early web in IRC chatrooms, online forums, and fledgling tech blogs, soaking in every byte of knowledge from the late '90s and early 2000s internet boom. That fascination with tech didn’t just stick. It evolved into a full-blown calling. After graduating with a degree in Journalism, he began his writing career at the dawn of Web 2.0. What started with small editorial roles and freelance gigs soon grew into a full-fledged career. He has since collaborated with global tech leaders, lending his voice to content that bridges technical expertise with everyday usability. He’s also written annual reports for Globe Telecom and consumer-friendly guides for VPN companies like CyberGhost and ExpressVPN, empowering readers to understand the importance of digital privacy. His versatility spans not just tech journalism but also technical writing. He once worked with a local tech company developing web and mobile apps for logistics firms, crafting documentation and communication materials that brought together user-friendliness with deep technical understanding. That experience sharpened his ability to break down dense, often jargon-heavy material into content that speaks clearly to both developers and decision-makers. At the heart of his work lies a simple belief: technology should feel empowering, not intimidating. Even if the likes of smartphones and AI are now commonplace, he understands that there's still a knowledge gap, especially when it comes to hardware or the real-world benefits of new tools. His writing hopes to help close that gap. Cedric’s writing style reflects that mission. It’s friendly without being fluffy and informative without being overwhelming. Whether writing for seasoned IT professionals or casual readers curious about the latest gadgets, he focuses on how a piece of technology can improve our lives, boost our productivity, or make our work more efficient. That human-first approach makes his content feel more like a conversation than a technical manual. As his writing career progresses, his passion for tech journalism remains as strong as ever. With the growing need for accessible, responsible tech communication, he sees his role not just as a journalist but as a guide who helps readers navigate a digital world that’s often as confusing as it is exciting. From reviewing the latest devices to unpacking global tech trends, Cedric isn’t just reporting on the future; he’s helping to write it. View all articles by Cedric Solidon Our editorial process The Tech Report editorial policy is centered on providing helpful, accurate content that offers real value to our readers. We only work with experienced writers who have specific knowledge in the topics they cover, including latest developments in technology, online privacy, cryptocurrencies, software, and more. Our editorial policy ensures that each topic is researched and curated by our in-house editors. We maintain rigorous journalistic standards, and every article is 100% written by real authors.