Question 1

Can I start with a VPS and migrate to DGX Spark later?

Accepted Answer

Yes. NemoClaw’s configuration is portable. Your YAML policies, privacy router routing tables, and OpenShell sandbox configurations transfer directly from a VPS deployment to DGX Spark hardware. The migration is a re-deployment with the same configuration files on new hardware, plus adding the local inference endpoint to your privacy router configuration. No policy rewrite required. This is the most common path for organizations that start with evaluation and graduate to production.

Question 2

Can NemoClaw run on AWS, Azure, or GCP GPU instances?

Accepted Answer

Yes. Cloud providers offer GPU-attached instances (AWS p4d/p5, Azure NC-series, GCP A2/A3) that provide NVIDIA GPU inference capability. This gives you local inference within the cloud provider’s data center — your data does not leave the cloud provider, but it does not stay on your physical premises either. For organizations where “data residency” means “within our cloud tenancy” (not “on our physical hardware”), cloud GPU instances provide a viable middle path. Cost is significantly higher than VPS — GPU cloud instances run $1,000–$5,000+/month.

Question 3

Does ManageMyClaw support all three hardware paths?

Accepted Answer

Yes. ManageMyClaw deploys NemoClaw on VPS infrastructure, DGX Spark hardware, RTX workstations, DGX Stations, and cloud GPU instances. The $2,500 Assessment includes a hardware recommendation based on your compliance requirements, team size, and budget model. Implementation pricing ($15,000–$45,000) is the same regardless of hardware — the policy configuration, sandbox hardening, and compliance documentation work is identical.

Question 4

Is the DGX Spark loud enough for an office environment?

Accepted Answer

The Dell Pro Max GB10 is designed as a desktop workstation, not a rack-mount server. Fan noise is comparable to a high-end desktop PC under load — audible but not disruptive in an office environment. For server-room deployments, noise is not a factor. For under-desk deployment in a quiet office, test with your specific workload before committing to placement.

Question 5

What happens when NemoClaw moves from alpha to general availability?

Accepted Answer

NemoClaw is in alpha as of March 2026. NVIDIA has been transparent about this. When NemoClaw reaches GA, hardware requirements may change — particularly minimum GPU specifications for local inference. Organizations that deploy on DGX Spark or RTX 4090/5090 hardware today are positioned for the GA transition, as these GPUs exceed likely minimum requirements. VPS deployments are unaffected by GPU requirement changes since they do not run local inference. Our Architecture Deep Dive tracks NemoClaw’s evolution as NVIDIA releases updates.

Question 6

Can I run multiple NemoClaw instances on one DGX Spark?

Accepted Answer

Yes, with caveats. Multiple NemoClaw instances can share the GB10 Superchip’s GPU for inference, but each instance needs its own CPU and RAM allocation. With the DGX Spark’s hardware profile, running 2–3 concurrent NemoClaw instances is practical for department-level deployments. Beyond that, GPU memory contention affects inference latency. For multi-department deployments requiring 5+ concurrent instances, the DGX Station’s multi-GPU architecture is the appropriate hardware tier.

Tag: VPS

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