The Microsoft Surface Laptop Ultra shows where the future of Artificial Super Intelligence is heading. Not only in the cloud, but also working directly on-device.This hardware shift will lead to less regulation of how tech is used on-device, moving the regulatory focus almost entirely to how models are trained in datacenters—whether those datacenters are on Earth or in space.
I have always aksed what people would use with this much RAM, and Microsoft FINALLY answered my simple question.Running models on-device gives you the headroom you need to make and edit videos and game—the two most common answers to why anyone needs that much power. So of course this machine is going to be expensive, but it comes properly equipped: it is storage upgradable and has good I/O, including a USB-A port, a headphone jack, and a microSD card slot.
Here is how Microsoft builds around that spec sheet:
“Designed around NVIDIA RTX Spark, Surface Laptop Ultra unites an NVIDIA Blackwell RTX GPU with up to 6,144 cores, an NVIDIA Grace CPU with up to 20 cores, and up to 128 GB of unified memory. Run AI models exceeding 120B parameters locally, with up to 1 petaflop of AI performance. Move between creative work, development, and immersive gaming without missing a beat. Keep more of your work on-device, with less reliance on the cloud and access to the CUDA ecosystem and full Windows AI stack.”
“Creative professionals get a display they can trust, graphics acceleration when projects get demanding, and up to 128 GB of unified memory to provide headroom for multitasking across demanding creative and local AI workflows. Developers can use local models with GitHub Copilot to bring agentic coding on device. They can prototype agents, review code, test larger models, and keep development tools running side by side. When the work is done, the same RTX Spark architecture that accelerates creative and AI workloads also powers a great gaming experience.”
The neat part is how Microsoft handles running agents right where they work best:
“Give developers the freedom to move faster with agents, while keeping access, compute, and cost under control. Windows is the OS for agents, and Surface is the hardware for Windows. Microsoft Execution Containers provide containment for agents, while upcoming Windows capabilities will use Microsoft Entra to distinguish agent activity from user activity and extend Microsoft Agent 365 controls to local agents on-device. With NVIDIA RTX Spark and up to 128 GB of unified memory, Surface Laptop Ultra and Surface RTX Spark Dev Box can run demanding models and agent workflows locally, including GitHub Copilot tasks that investigate builds and propose fixes, while Microsoft Dev Box adds cloud capacity when needed. The result is governed, scalable AI development without spending a cloud token on every step.”
Alongside the laptop, there is also a nearly $6,000 AI box—the Surface RTX Spark Dev Box:
- Up to 1 petaflop of AI performance and 128 GB of unified memory on your desk
- Support for AI models exceeding 120B parameters with large context windows
- Local inference, evaluation, and experimentation at interactive speeds
- The same powerful NVIDIA RTX Spark platform that powers Surface Laptop Ultra
That is what is so cool to me. We can already run models on our devices right now, but building hardware from the ground up for this tech means you don’t have the over-a-minute wait time that I had running Jan AI on my PC versus Google Gemini in the cloud.
I predicted that we would see something like on-device AI centers in our own homes, and with this lineup, that future is officially here. God bless and Tech Talk To You Later!!!
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