Engineered for Agentic AI: NVIDIA HGX B300 on CoreWeave Cloud

Introducing NVIDIA HGX B300 on the Essential Cloud for AI

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As demand for agentic AI accelerates the shift toward inference workloads, cloud infrastructure requirements are evolving significantly. Long context windows require expanded memory. Multi-reasoning drives sustained GPU utilization. Agent coordination depends on low-latency, high-bandwidth interconnects across large-scale clusters. Running agentic AI at scale requires powerful accelerators combined with an AI-native cloud that delivers consistent performance, operational visibility, and scalability. Today, we are proud to announce that NVIDIA HGX B300 is now generally available on CoreWeave Cloud, with AI pioneers like Cursor already moving toward production workloads. NVIDIA HGX B300 doubles interconnect speed with NVIDIA Quantum-X800 InfiniBand networking, NVIDIA BlueField-3 data processing units (DPUs), and 800 Gbps NVIDIA ConnectX-8 SuperNICs, enhancing NVFP4 inference performance, and increasing GPU memory capacity by 50% over the NVIDIA HGX B200. CoreWeave unlocks NVIDIA HGX B300 at scale, with our benchmarks demonstrating 3.42x faster token generation on Kimi K2.5 and 4.93x faster end-to-end request latency on DeepSeek-R1 (vs. NVIDIA HGX H200). This milestone marks another step forward in advancing agentic AI—powered by an AI cloud that unlocks the performance of the latest-generation GPUs and backed by our relentless commitment to trusted partnership, unmatched speed, and validated performance for every AI pioneer.

Why AI pioneers like Cursor and Decart AI partner with CoreWeave for NVIDIA HGX B300 For organizations building agentic AI, where long-context inference, multi-step reasoning, and distributed coordination amplify infrastructure risk, a trusted partner is non-negotiable. CoreWeave provides direct-to-expert support that evolves alongside rapidly changing model architectures, across multiple generations of accelerators. Customers like Mistral have praised this hands-on support, noting that it allows their team to run jobs overnight with confidence and frees them to focus on building models.

Our support is why AI leaders such as Cursor and Decart AI choose CoreWeave Cloud for the latest NVIDIA GPUs: "We’ve already run production workloads with CoreWeave on NVIDIA HGX B200, and that experience built real confidence in their ability to operate at scale. What mattered to us was predictable performance, operational reliability, and having a partner who could support us as our requirements evolved. As we move toward B300, that proven operating model and continuity in execution give us confidence to focus on building more capable AI code generation systems, rather than worrying about infrastructure risk." — Aman Sanger, Co-founder, Cursor "At Decart, we transform video from a static medium into a living, responsive world experience. Our partnership with CoreWeave has enabled us to run NVIDIA HGX B200 at production scale and push the boundaries of training and inference, while delivering seamless interactive video experiences via the CoreWeave stack. With the NVIDIA HGX B300 and the upcoming NVIDIA Vera Rubin platform, we are effectively enabling a new level of massively scalable real-time generative and agentic AI." — Orian Leitersdorf, Chief Scientist, Decart CoreWeave’s direct-to-expert support reduces uncertainty, accelerates deployment, and ensures performance scales as workloads grow more complex. Accelerated pace that drives breakthroughs Agentic AI development is iterative: models must be evaluated, fine-tuned, and orchestrated across agents in continuous development loops. An infrastructure platform must reduce this friction across the entire cycle. Early, production-grade signals—along with the tools and operational visibility to act on them—are critical for reducing inefficiencies in agentic AI development. This is exactly what CoreWeave Mission Control™ provides, while shifting the responsibility for maintaining NVIDIA HGX B300 cluster health from your team to ours. NVIDIA HGX B300 instances are natively integrated with our advanced fleet lifecycle controllers. This ensures rapid, AI-native provisioning and orchestration, ensuring high availability that allows you to begin training or fine-tuning with NVIDIA HGX B300 within hours, not weeks. This reduces time lost to infrastructure setup and manual coordination. We also provide a real-time, deep view of NVIDIA HGX B300 instance performance, delivering actionable insights into NVIDIA NVLink performance, GPU utilization, and other key metrics. To accelerate the development pace even further, CoreWeave provides a Kubernetes-native orchestration layer purpose-built for large-scale distributed AI systems, CoreWeave Kubernetes Service (CKS). CKS enables you to deploy, scale, and manage agent workflows with production-grade reliability and tight GPU integration. Slurm on Kubernetes (SUNK) extends this by allowing you to run more experiments in parallel while maximizing GPU efficiency. For evaluation and debugging, W&B Weave provides the tooling needed to iterate on agentic AI systems. With end-to-end tracing of agent runs, developers can visualize and inspect the full agentic system to diagnose and remediate those failures that occur in intermediate reasoning steps. Agentic AI also needs fast, scalable, and predictable data access to execute multi-stage reasoning and frequent checkpoints. CoreWeave AI Object Storage offers just that, with speeds of up to 7 GB/s per GPU, keeping NVIDIA Blackwell Ultra GPUs fed so they aren’t idle waiting on networking or storage I/O. For agentic AI, pace is not just about faster provisioning, but about shortening the time between idea, experiment, validation, and production. CoreWeave’s AI-native platform ensures NVIDIA HGX B300 delivers not only raw capability but also the operational velocity required to capitalize on it with 96% goodput. This means nearly all requested compute translates directly into useful work, ultimately helping you outpace competitors and bring innovations to market faster. Engineered for performance NVIDIA HGX…