Many businesses rely on hosted AI services, but pay-as-you-go billing can make it difficult to manage costs—especially when it comes to agentic development. AI agents typically consume more resources than traditional chat-based interactions, and because they act autonomously, it’s harder to plan and control their resource usage.
Dell’s deskside agentic AI systems offer another approach, allowing developers to test and develop on local hardware powered by NVIDIA’s Grace Blackwell architecture, without racking up external API costs.
The Dell Pro Precision with GB10 is a compact deskside workstation designed for individual developers and small teams, while the GB300 is a larger tower system suitable for heavier workloads with higher concurrency. Choose the one that’s appropriate for your needs, and you can replace variable consumption costs with a predictable infrastructure investment.
TL;DR
- Agentic AI software runs persistently and can trigger multi-step tasks, leading to unpredictable resource usage
- The Dell Pro Precision with GB10 lets developers test and iterate locally, without incurring per-token costs
- The powerful Dell Pro Precision with GB300 can support larger models, heavier workloads, and greater concurrency
- Deskside AI can also reduce latency and give businesses more control of where data is stored and processed
- An appropriate deskside system can help to manage costs while giving developers dedicated access to the resources they need
Why are agentic AI development costs so hard to predict?
For individual chat or API-based interactions, usage-based AI costs are relatively predictable.
AI agents typically consume more resources than traditional chat-based interactions, and because they act autonomously, it’s harder to plan and control their resource usage
With agentic AI, these costs are much harder to estimate, as agents may run persistently and can autonomously trigger complex multi-step operations. This can lead to a higher base level of AI usage and unplanned spikes in demand, creating a financial liability for businesses using outsourced AI services.
For frequent or persistent workloads, local AI can often deliver lower and more predictable running costs. The key is choosing the right local AI platform, ensuring the initial infrastructure investment matches anticipated requirements.
How can the Dell Pro Precision with GB10 reduce the cost of agentic AI development?
The Dell Pro Precision with GB10 allows developers working on agentic AI projects to iterate as much as is needed to get the best results, without having to worry about growing costs as each iteration incurs an incremental per-token charge. In fact, Dell analysis shows organizations investing in deskside AI can break even against public cloud API costs in as little as three months for the Dell Pro Precision with GB300.
What kinds of agentic workloads are suitable for the Dell Pro Precision with GB10?
The Dell Pro Precision with GB10 is designed to support individuals and small development teams. It offers up to 1 petaFLOP of FP4 AI performance and 128GB of unified memory, is capable of hosting AI models with up to 200 billion parameters, and can support up to eight concurrent agents. This allows for multi-agent experimentation without relying on cloud AI or a shared GPU infrastructure.
How the Dell Pro Precision with GB300 makes persistent inference costs more predictable
The Dell Pro Precision with GB300 is a more powerful system offering data center-class deskside AI performance. It can support multi-step agentic workflows for entire teams, without accumulating the external per-token charges that would otherwise accompany persistent AI applications.
When is the Dell Pro Precision with GB300 more suitable than a GB10 system?
The Dell Pro Precision with GB300 supports larger models than the GB10, with support for up to one trillion parameters along with up to 150 concurrent agents. This makes it suitable for agentic tasks involving longer contexts, multi-step workflows, local fine-tuning, and dense multi-agent execution. The core hardware is significantly more capable than the Dell Pro Precision with GB10, offering 20 petaFLOPS of FP4 performance with 748GB of memory (496GB LPDDR5X system memory plus 252GB HBM3e GPU memory) and up to 16TB of local storage.
Deskside AI helps businesses keep control of workloads and data
As well as helping to manage costs, deskside systems allow data to be kept close to AI engines, reducing latency for developers and giving businesses direct control of where information is stored and processed. Compared to shared GPU infrastructure, developers can also benefit from dedicated local access to AI resources, helping them to plan and execute sustained workloads. And because Dell supports the NVIDIA agentic ecosystem, developers can make use of agent-specific tools such as NVIDIA NemoClaw and NVIDIA OpenShell.
Specification |
Dell Pro Precision with GB10 |
Dell Pro Precision with GB300 |
|---|---|---|
AI platform |
NVIDIA GB10 Grace Blackwell superchip |
NVIDIA GB300 Grace Blackwell Ultra desktop superchip |
CPU |
20-core Arm CPU |
72-core Arm CPU |
FP4 AI performance |
Up to 1 petaFLOPS |
Up to 20 petaFLOPS |
Memory |
Up to 128GB |
748GB |
Local storage |
Up to 4TB SSD |
Up to 16TB SSD |
Model size |
Up to 200B parameters |
Up to 1T parameters |
Concurrent agents |
Up to 8 |
Up to 150 |
Is the Dell Pro Precision with GB10 or GB300 right for my business?
The answer to that depends on your anticipated requirements. The Dell Pro Precision with GB10 is a good fit for relatively modest model sizes and workloads, while the Dell Pro Precision with GB300 is suitable for heavier loads with more concurrency and sustained inferencing. Businesses seeking a scalable option should also consider Dell Pro Precision tower workstations, which can support models from 30 billion to 500 billion parameters.
Whichever you choose, the goal isn’t necessarily to bring all AI workloads in-house, but to place each workload in the most appropriate place. Local AI development isn’t always cheaper than using cloud resources, but Dell analysis suggests that deskside agentic AI can deliver up to an 87% cost saving versus cloud APIs over two years.
At the same time, businesses gain a more predictable cost base, more consistent access to AI resources, and overall better control of their own data.
If you think Dell Pro Precision with GB10 or Dell Pro Precision with GB300 are the right solutions for your AI development workflows, find out more on the Dell website.
FAQs
How does the Dell Pro Precision with GB10 help control AI development costs?
The Dell Pro Precision with GB10 lets developers test and iterate on agentic AI projects locally, avoiding the per-token charges that come with cloud-based API usage, with Dell analysis showing a break-even point as fast as three months (for the Dell Pro Precision with GB300).
What's the difference between the Dell Pro Precision with GB10 and GB300?
The Dell Pro Precision with GB10 is built for individual developers and small teams, supporting models up to 200 billion parameters and 8 concurrent agents. The Dell Pro Precision with GB300 is a more powerful system designed for larger teams, supporting up to one trillion parameters and 150 concurrent agents.
Is local AI development always cheaper than using the cloud
Not always, but for frequent or persistent workloads, Dell analysis suggests deskside agentic AI can deliver up to an 87% cost saving over two years compared to public cloud APIs.