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In a major boost to the GPU cloud ecosystem, NVIDIA and Amazon Web Services announced a joint effort to add two million additional GPUs to the market, alongside next‑generation infrastructure designed for "agentic" and physical AI workloads. This partnership promises to dramatically increase the compute resources available to developers, enterprises, and AI research teams, reinforcing the dominance of cloud‑based GPU acceleration.
Key developments:
- The AWS‑NVIDIA collaboration will make a massive 2 million GPU expansion possible, delivering the latest high‑performance hardware to a broader set of cloud regions and services.
- Simultaneously, pricing data released in October 2026 shows that the on‑demand cost for an NVIDIA H100 80GB GPU varies widely across providers, with the cheapest U.S. rate at $6.88 per GPU‑hour on AWS (p5.48xlarge) and competitive offerings from CoreWeave at $6.16 per GPU‑hour for an 8‑GPU node.
- CoreWeave has also integrated NVIDIA’s newest Vera Rubin NVL72 GPU and Vera CPU, with the company’s Cognition platform becoming the first production‑grade customer running agentic AI workloads on this architecture.
Why it matters:
- Scale for AI breakthroughs: The two‑million‑GPU boost addresses current supply constraints, enabling larger model training runs, faster inference, and more extensive experimentation for generative AI, scientific computing, and simulation.
- Cost‑effective access: By normalizing pricing across providers, the market now offers clearer cost comparisons, helping users choose the most economical option for their workloads. The modest price differential between AWS and CoreWeave suggests healthy competition that can drive down overall cloud GPU costs.
- Next‑gen infrastructure: The integration of Vera Rubin chips and the Vera CPU signals a shift toward hardware optimized for agentic AI, which promises more efficient execution of complex reasoning and autonomous tasks.
What to watch next:
- Deployment timelines: Tracking when the additional GPUs become available across AWS regions and how quickly CoreWeave scales its Vera Rubin offerings.
- Pricing evolution: Monitoring whether competitive pressures drive further reductions in H100 and future GPU pricing, especially as newer architectures like the GB200 and H200 enter the market.
- Ecosystem adoption: Observing how AI startups, research institutions, and enterprise AI teams adopt the expanded GPU pool and the Vera Rubin platform for production workloads.
Together, these developments mark a pivotal moment for GPU cloud services, positioning the industry to meet the surging demand for high‑performance AI compute while offering more transparent and competitive pricing options. [[1, 2, 3]]