CoreWeave, Inc. (NASDAQ:CRWV), The Essential Cloud for AI™, today announced an expansion of its purpose-built AI cloud platform at NVIDIA's GTC conference. The expansion brings NVIDIA HGX B300 to the CoreWeave Cloud, unlocking a new generation of performance for AI workloads, alongside new Weights & Biases capabilities that streamline reinforcement learning (RL) and agent development workflows."The next phase of AI is being defined by how efficiently AI systems can run and scale in production," said Michael Intrator, CEO, co-founder, and chairman at CoreWeave. "By pairing the massive compute power of NVIDIA's latest hardware with CoreWeave's cloud services, we're enabling enterprises to build and refine autonomous agents faster and more reliably than ever before. This expansion reinforces our position as the essential partner for any organization navigating the complexities of frontier-scale AI."

"The era of AI is shifting from training models to operating agents at scale," said Jensen Huang, founder and CEO, NVIDIA. "CoreWeave is a world-class new generation AI-Native cloud. We are thrilled to partner with them to build out NVIDIA computing infrastructure to power the world's AI."

Purpose-Built for Agentic AI: NVIDIA HGX B300

CoreWeave Cloud unlocks NVIDIA HGX B300 performance at scale, marking a major step forward for frontier and agentic workloads. With the general availability of NVIDIA HGX B300, part of the NVIDIA Blackwell Ultra platform, customers will have access to:

  • Performance Leap: NVIDIA HGX B300 is designed for AI reasoning and inference with enhanced compute and increased memory.
  • Massive Memory: Featuring 2.1 TB of HBM3e memory—a 50% increase over HGX B200 instances—enabling teams to run long-context inference with low latency and train models with 100B+ parameters on a single node.
  • Unprecedented Bandwidth: Next-generation NVIDIA Quantum-X800XDR InfiniBand support doubles node-to-node bandwidth, eliminating interconnect bottlenecks.
  • Liquid-Cooled Reliability: Every HGX B300 server on CoreWeave Cloud is managed by state-of-the-art liquid cooling to eliminate thermal throttling and allow sustained peak performance.

"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," said Aman Sanger, Co-Founder of Cursor, an AI-powered code editor. "We're focused on collaborating with companies who deliver predictable performance, operational reliability, and ongoing support as our requirements evolve. As we move toward HGX B300, that proven operating model gives us confidence to focus on building more capable AI code generation systems rather than infrastructure risk."

CoreWeave also expects to be among the first cloud providers to deploy the NVIDIA Vera Rubin NVL72 platform and NVIDIA Vera CPU rack in production in the second half of 2026. This expansion will further support large-scale inference, reasoning, and the most demanding agentic AI applications.

Direct "On-the-Job" Training for Agents with Environment-Free RL

RL is the most effective method for post-training LLMs on agentic tasks, but it traditionally requires costly, time-consuming, and difficult-to-model simulated environments. Weights & Biases now addresses this with environment-free training in its Serverless RL offering, eliminating the need to build simulated environments, and allowing agents to learn through continual "on-the-job" training.

  • Efficiency: Achieve 1.4x faster training at up to 40% lower cost compared to self-managed clusters.
  • Superior Results: Deliver inference with up to 5x lower cost and up to 60x lower latency without quality loss.

Production Agent Evaluations Accelerate Agent Development

Research evaluations often rely on limited datasets and synthetic scenarios, leaving agents unprepared for real-world production. This gap makes it difficult to feed production insights back into the research loop, slowing time-to-market and resulting in agents that fail to meet expectations.

Production agent evaluations in W&B Weave close that gap, connecting research and production, enabling teams to learn from real user interactions. It automatically detects production failure modes, alerts researchers, and feeds insights back to improve evaluation datasets and accelerate iteration. By closing this loop, W&B Weave helps teams ship more reliable agents faster.

  • Agent Self-Improvement: Incoming traces are automatically scored by LLM judges. Lower-quality outputs are routed for human review and turned into test cases, making evaluation suites smarter over time. Specialized classifier models then analyze the production traces and identify failure modes.
  • Accelerated Development: Smart alerts notify when new failure modes are detected, allowing customers to refine agents in production using data from real user interactions and continuous monitoring.

Accelerating Robotics AI Development

W&B Models now allows robotics and embodied AI customers to track, compare, and reproduce multimodal experiments faster. Teams can log training metrics, simulation outputs, and video in a single workspace, and use a new comparison panel to evaluate up to four images or videos side-by-side. In collaboration with NVIDIA, Weights & Biases is releasing two blueprints for scalable training of RL and Vision-Language-Action (VLA) models using NVIDIA Isaac Lab simulations. These blueprints outline a full-stack workflow to help teams quickly start training and fine-tuning embodied AI models.

Monitor Training Anywhere With the First Weights & Biases Mobile App

To enable AI pioneers to manage these massive production runs from anywhere, CoreWeave introduced the first iOS app designed specifically for AI model development. The Weights & Biases iOS app provides a mobile-first experience to track training runs in real time, allowing researchers to spot issues early and make confident decisions without being tethered to a desktop.

CoreWeave's AI cloud delivers industry-leading performance and efficiency through an end-to-end technology stack optimized for AI workloads. It has achieved top MLPerf benchmark for AI workloads, Platinum rankings in both SemiAnalysis ClusterMAX™ 1.0 and 2.0, and NVIDIA Exemplar Cloud validation for training and inference on GB200 NVL72. Visit us at booth #913 at NVIDIA GTC to learn more about today's announcements.