NVIDIA and Google Cloud have collaborated for more than a decade, co‑engineering a full‑stack AI platform that spans every technology layer — from performance‑optimized libraries and frameworks to enterprise‑grade cloud services. This foundation enables developers, startups and enterprises to push agentic and physical AI out of the lab and into production — from agents that […]
Artificial intelligence has rapidly emerged as one of the most critical workloads in modern computing. For the vast majority of enterprises, this workload runs on Kubernetes, an open source platform that automates the deployment, scaling and management of containerized applications. To help the global developer community manage high-performance AI infrastructure with greater transparency and efficiency, […]
The NVIDIA Blackwell platform has been widely adopted by leading inference providers such as Baseten, DeepInfra, Fireworks AI and Together AI to reduce cost per token by up to 10x. Now, the NVIDIA Blackwell Ultra platform is taking this momentum further for agentic AI. AI agents and coding assistants are driving explosive growth in software-programming-related
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Today, Mistral AI announced the Mistral 3 family of open-source multilingual, multimodal models, optimized across NVIDIA supercomputing and edge platforms. Mistral Large 3 is a mixture-of-experts (MoE) model — instead of firing up every neuron for every token, it only activates the parts of the model with the most impact. The result is efficiency
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At AWS re:Invent, NVIDIA and Amazon Web Services expanded their strategic collaboration with new technology integrations across interconnect technology, cloud infrastructure, open models and physical AI. As part of this expansion, AWS will support NVIDIA NVLink Fusion — a platform for custom AI infrastructure — for deploying its custom-designed silicon, including next-generation Trainium4 chips for
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Where CPUs once ruled, power efficiency — and then AI — flipped the balance. Extreme co-design across GPUs, networking and software now drives the frontier of science.
At SC25, NVIDIA unveiled advances across NVIDIA BlueField DPUs, next-generation networking, quantum computing, national research, AI physics and more — as accelerated systems drive the next chapter in AI supercomputing. NVIDIA also highlighted storage innovations powered by the NVIDIA BlueField-4 data processing unit, part of the full-stack BlueField platform that accelerates gigascale AI infrastructure. More
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At the OCP Global Summit, NVIDIA is offering a glimpse into the future of gigawatt AI factories. NVIDIA will unveil specs of the NVIDIA Vera Rubin NVL144 MGX-generation open architecture rack servers, which more than 50 MGX partners are gearing up for along with ecosystem support for NVIDIA Kyber, which connects 576 Rubin Ultra GPUs,
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Microsoft Azure today announced the new NDv6 GB300 VM series, delivering the industry’s first supercomputing-scale production cluster of NVIDIA GB300 NVL72 systems, purpose-built for OpenAI’s most demanding AI inference workloads. This supercomputer-scale cluster features over 4,600 NVIDIA Blackwell Ultra GPUs connected via the NVIDIA Quantum-X800 InfiniBand networking platform. Microsoft’s unique systems approach applied radical engineering
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NVIDIA Blackwell is the core of an entire system architecture designed specifically to power AI factories that produce intelligence through inference using the largest and most complex AI models.
AI reasoning, inference and networking will be top of mind for attendees of next week’s Hot Chips conference. A key forum for processor and system architects from industry and academia, Hot Chips — running Aug. 24-26 at Stanford University — showcases the latest innovations poised to advance AI factories and drive revenue for the trillion-dollar
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The integration of quantum processors into tomorrow’s supercomputers promises to dramatically expand the problems that can be addressed with compute — revolutionizing industries including drug and materials development. In addition to being part of the vision for tomorrow’s hybrid quantum-classical supercomputers, accelerated computing is dramatically advancing the work quantum researchers and developers are already doing
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NVIDIA is working with companies worldwide to build out AI factories — speeding the training and deployment of next-generation AI applications that use the latest advancements in training and inference. The NVIDIA Blackwell architecture is built to meet the heightened performance requirements of these new applications. In the latest round of MLPerf Training — the
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Over a century ago, Henry Ford pioneered the mass production of cars and engines to provide transportation at an affordable price. Today, the technology industry manufactures the engines for a new kind of factory — those that produce intelligence. As companies and countries increasingly focus on AI, and move from experimentation to implementation, the demand
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TSMC, Cadence, KLA, Siemens and Synopsys are advancing semiconductor manufacturing by adopting the NVIDIA CUDA-X and NVIDIA Blackwell platforms. NVIDIA Blackwell GPUs, NVIDIA Grace CPUs, high-speed NVIDIA NVLink fabrics and switches, and domain-specific NVIDIA CUDA-X libraries like NVIDIA cuDSS and NVIDIA cuLitho are improving computational lithography and device simulation for advanced chip manufacturing. “Our collaboration
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Traditionally, data centers have relied on air cooling — where mechanical chillers circulate chilled air to absorb heat from servers, helping them maintain optimal conditions. But as AI models increase in size, and the use of AI reasoning models rises, maintaining those optimal conditions is not only getting harder and more expensive — but more
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In the latest MLPerf Inference V5.0 benchmarks, which reflect some of the most challenging inference scenarios, the NVIDIA Blackwell platform set records — and marked NVIDIA’s first MLPerf submission using the NVIDIA GB200 NVL72 system, a rack-scale solution designed for AI reasoning. Delivering on the promise of cutting-edge AI takes a new kind of compute
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AI is fueling a new industrial revolution — one driven by AI factories. Unlike traditional data centers, AI factories do more than store and process data — they manufacture intelligence at scale, transforming raw data into real-time insights. For enterprises and countries around the world, this means dramatically faster time to value — turning AI
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AI reasoning models and agents are set to transform industries, but delivering their full potential at scale requires massive compute and optimized software. The “reasoning” process involves multiple models, generating many additional tokens, and demands infrastructure with a combination of high-speed communication, memory and compute to ensure real-time, high-quality results. To meet this demand, CoreWeave
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DeepSeek-R1 is an open model with state-of-the-art reasoning capabilities. Instead of offering direct responses, reasoning models like DeepSeek-R1 perform multiple inference passes over a query, conducting chain-of-thought, consensus and search methods to generate the best answer. Performing this sequence of inference passes — using reason to arrive at the best answer — is known as
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