NVIDIA and Oracle have teamed up with the U.S. Department of Energy to build what may become the most powerful AI supercomputer at a national lab. The main system, Solstice, will use a staggering 100,000 NVIDIA Blackwell GPUs. This is not just another data-centre upgrade — it’s designed to speed up scientific research, from climate models to new materials and medicine.
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What is Solstice?
Think of Solstice as a gigantic AI engine. It’s a cluster of GPUs (special processors that AI uses very well) connected with very fast networking and software tools. The goal is to let researchers train and run huge AI models faster than ever. The DOE calls this part of a wider push to give scientists powerful tools to discover new things.
Who’s Involved?
- NVIDIA supplies the GPUs — the new Blackwell family — and the AI software stack.
- Oracle brings cloud infrastructure and enterprise-grade systems, linking Solstice into a larger Oracle Cloud fabric.
- DOE & Argonne host and manage the systems so public researchers can use them for science.
How big is “100,000 GPUs”?
It’s hard to picture, but here’s a quick way to think about it: modern large language models need thousands of GPUs to train. Solstice’s 100,000 Blackwell GPUs means researchers can train far larger models, or train many experiments in parallel. The announcement also pairs Solstice with a smaller system, Equinox, which will have 10,000 Blackwell GPUs and is expected in the first half of 2026. Together, these systems aim to deliver massive AI performance.
Expected performance
NVIDIA says the combined new systems will deliver huge AI compute measured in exaflops — the rough headline number mentioned is about 2,200 exaflops of AI performance across several systems being built with partners. That’s a level of raw compute designed specifically for large AI model training and complex scientific simulations.
Why this matters for AI and AGI discussions
People often ask: will more GPUs bring us closer to Artificial General Intelligence (AGI)? In response, more compute is a major ingredient but not the whole recipe. Tools like Solstice let researchers run experiments that were impossible before — bigger models, richer simulations, and deeper scientific workflows. These help push the limits, but AGI depends on many things: algorithms, data, safety research, and policy. Still, this kind of infrastructure is a clear step toward more ambitious AI research.
What experts are saying
Jensen Huang, NVIDIA’s founder and CEO, described this as an “engine for discovery,” saying the systems will give researchers access to advanced AI infrastructure for work across healthcare, materials and energy. DOE officials termed the partnership as a practical way to accelerate U.S. scientific leadership.
What this means for cloud infrastructure and Oracle Cloud
Oracle’s role shows how cloud providers are moving beyond offering instances to building entire AI fabrics. Oracle Cloud’s high-scale networking and data-centre know-how are part of how these gigantic GPU clusters will be stitched together and made usable for researchers and agencies. For businesses and cloud watchers, this highlights a shift: cloud infrastructure is becoming the backbone for national-scale AI projects.
Even if you’re not a researcher, projects like Solstice matter. Faster AI research can lead to better models for weather prediction, healthcare diagnostics, energy efficiency, and more — all areas that affect everyday life.
Sources: NVIDIA press release, U.S. Department of Energy announcement, Argonne National Laboratory article, and news coverage summarising the Solstice/Equinox plans. :contentReference[oaicite:16]{index=16}
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