5 ways to cut AI costs and speed up development using the Dell Pro Max with GB10

Enterprise AI is evolving quickly—not just in what it can do, but how it is being developed. Alongside familiar chat sessions and data analysis jobs, businesses are developing new AI-assisted applications and research workflows. For certain workloads, cloud-based services can be inefficient, especially where usage is paid for on a per-token basis.

As a result, there’s a growing focus on local and hybrid deployments. And alongside on-premises AI servers, businesses are turning to deskside systems that transform the workstation from a productivity device into a personal AI development and execution platform.

The Dell Pro Max with GB10 is a compact, purpose-built deskside AI accelerator built around the NVIDIA GB10 Grace Blackwell superchip. It’s a new product that, alongside its big sister the Dell Pro Max with GB300 and close relatives in the Pro Precision desktop workstations, sits within Dell's Deskside Agentic AI product lineup.

The GB10 offers enterprise-grade inference with compute power that’s far beyond a typical on-device NPU, and it integrates with the Dell AI Factory with NVIDIA platform to support workload mobility and scaling. In this article, we’ll look at five ways that these two Dell solutions can help businesses cut costs and speed up development.

TL;DR

• Local inference can be highly cost-efficient, but it’s best implemented as part of a hybrid AI architecture
• Deskside AI systems help developers to be productive, and support research and experimentation
• A unified development platform enables businesses to painlessly scale up development projects into enterprise deployments
• Keeping AI data and models on a local workstation helps avoid potential data-protection issues
• A flexible AI portfolio, including deskside options, lets businesses run every AI task in its most suitable place

1. Reduce AI costs with local inference

Running AI inference on local hardware means you don’t need to pay for the tokens used by each operation, as is typical with cloud AI platforms. This can add up to a significant saving over time, especially for agentic services that are continually processing context to make autonomous decisions.

Not every workload is suitable for local execution, however. The cloud still has potential advantages, including scalability and overall inferencing performance. The most flexible approach is a hybrid model that lets businesses place each AI workload in its most suitable location. The Dell Pro Max with GB10 runs the same NVIDIA DGX OS and AI software stack as production-scale servers, so it can operate as a standalone AI processing unit or fit seamlessly into a larger hybrid architecture.

2. Speed up AI development with local testing

Deskside AI capabilities allow developers to be more productive, as they can make use of dedicated compute resources with minimal latency. A local model also helps avoid bottlenecks outside of the AI system, such as shared storage and job queues.

Because there’s no need to worry about token quotas, deskside AI also empowers users to iterate and explore freely, helping them to make new discoveries, verify findings and spot errors. These advantages aren’t solely limited to developers—they can extend to researchers, data scientists and anyone else with specific AI requirements. As an independent reviewer at IT Pro puts it, a deskside solution such as the Dell Pro Max with GB10 provides “the freedom and flexibility to experiment with AI deployments within the enterprise.”

3. Scale AI projects without rebuilding your workflows

A consistent, unified AI platform allows test deployments to be scaled up into fully operational workflows with minimal upheaval.

Dell AI Factory with NVIDIA offers a standard architecture that provides the required consistency across deskside, data center and cloud AI deployments. Models and workflows developed on the Dell Pro Max with GB10 can be easily migrated to larger environments such as the Dell Pro Max with GB300—a more powerful deskside AI system designed for larger-scale workloads—or onto shared AI systems running in the data center or cloud. Coordinated orchestration of AI workloads helps businesses manage their resources and operations as requirements change.

4. Keep sensitive AI workloads on-premises

Keeping sensitive AI workloads on company-owned infrastructure gives organizations control over data, governance and compliance. It avoids any concerns that may arise from sharing information with a cloud AI service, and minimizes the security and operational risks that accompany data movement in general.

Deskside AI platforms such as the Dell Pro Max with GB10 are ideal for working with sensitive data or models, as they not only keep information on the company’s network but make it easier to lock down access to a single authenticated user. This gives businesses the flexibility to prioritize security and governance when placing AI workloads, while an overall hybrid architecture keeps cloud AI available for suitable applications.

5. Maximize AI efficiency with a flexible portfolio

The best way to optimize AI costs and performance is by allowing every workflow to run in the right place, from exploratory development to ongoing agentic activity and large-scale data crunching. The Dell AI Factory with NVIDIA supports this with a common infrastructure that allows for the orchestrated movement of workloads from deskside to data center, and from local development through to production-scale deployment.

Within this context, the Dell Pro Max with GB10 provides a versatile alternative to larger AI servers, helping businesses to match their resources to their AI needs, even as those needs change and grow.

There’s no one-size-fits-all platform for AI. Across different applications, businesses may wish to prioritize token economics, performance, governance, scalability or other considerations. That flexibility can be achieved through a consistent AI development and execution platform that’s designed for hybrid architectures: with the Dell Pro Max with GB10 and Dell AI Factory with NVIDIA, each AI project and workload can be placed in whatever location delivers the most business value.

If you think the Dell Pro Max with GB10 has a place in your AI development workflow, find out more on the Dell website: US readers click here.