DGX vs HGX: what is the difference?

DGX and HGX both describe eight GPU NVIDIA systems, but DGX is NVIDIA's own fully built and supported appliance while HGX is a reference baseboard design that NVIDIA licenses to OEM partners to build their own branded servers. A DGX system, such as the DGX B200, ships as a fixed configuration with NVIDIA handling hardware validation, driver certification, and direct support, which suits organizations that want a single vendor relationship and minimal configuration decisions. HGX based systems from vendors like Supermicro, Dell, HPE, and Lenovo use the same core 8 GPU NVLink connected baseboard and GPUs as DGX, but let the OEM choose the CPU, memory, storage, networking, and chassis design, which typically opens up more configuration options and more competitive pricing through multiple vendors bidding for the same underlying GPU technology. Performance for the GPU portion of the workload is essentially identical between a DGX and a comparable HGX system since both use the same NVLink domain and GPU silicon. The right choice often comes down to procurement preferences, existing vendor relationships, and how much configuration flexibility a data center team wants. Nanobase AI helps clients weigh DGX simplicity against HGX flexibility based on their existing infrastructure and support requirements.

Two products, the same underlying GPU technology

Performance on the GPU portion of any workload is essentially identical between a DGX and a comparable HGX system, since both use the same 8-GPU NVLink domain and the same GPU silicon — the difference is entirely in who builds, configures, and supports the rest of the machine.

Why the distinction exists at all

NVIDIA created HGX specifically so that server vendors could build their own branded, differentiated systems around the same validated GPU baseboard rather than every enterprise having to buy directly from NVIDIA. This lets OEMs compete on CPU choice, storage architecture, networking options, chassis design, and price, while NVIDIA still controls and validates the GPU-critical parts of the design (the baseboard, NVSwitch fabric, and GPU modules themselves).

Software, licensing, and support in practice

The GPU driver stack itself is identical across DGX and HGX since both run the same NVIDIA-certified drivers and CUDA versions, but the surrounding operational experience differs. DGX ships with NVIDIA AI Enterprise and orchestration tooling pre-integrated and validated as one package, with a single support line to call when something goes wrong anywhere in the stack. HGX-based systems place that integration work on the OEM, which usually still delivers a working, supported stack but may involve coordinating between the OEM and NVIDIA if an issue sits at the boundary between hardware and GPU software.

This matters most for organizations without a dedicated infrastructure team: a single-vendor DGX support relationship reduces the risk of finger-pointing between vendors during an incident, while a well-resourced infrastructure team may not value that consolidation enough to pay any DGX premium over a comparable HGX configuration.

Choosing between them in practice

1. If minimizing configuration decisions and vendor relationships matters most, DGX offers a single point of contact and a fixed, pre-validated design.
2. If specific CPU, memory, storage, or networking requirements exist that a fixed DGX configuration cannot meet, an HGX-based server from an OEM offers that flexibility.
3. If competitive pricing across multiple vendors is a priority, soliciting quotes for HGX-based systems from Supermicro, Dell, and HPE typically surfaces more price variation than a single DGX quote.
4. If the organization has an existing procurement relationship or support contract with a specific OEM, an HGX-based server from that vendor may integrate more smoothly into existing operations.
5. If the workload will scale into a larger multi-node cluster, confirm networking and orchestration compatibility either way, since both DGX and HGX systems support standard InfiniBand/Ethernet cluster scaling.

For how the specific OEMs building HGX systems compare, see Supermicro vs Dell vs HPE, and for what a fully built DGX system includes, see what the DGX B200 includes.

Frequently asked questions

Is HGX cheaper than DGX for the same GPU count?

It often is, since multiple OEMs compete for HGX-based business, but the comparison should include support terms and integration effort, not just sticker price, since DGX bundles a validated software stack and single-vendor support.

Do DGX and HGX systems use different GPUs?

No, both use the same NVIDIA data center GPUs (H100, H200, B200) in the same SXM form factor connected through the same NVLink and NVSwitch fabric; the distinction is entirely in the surrounding system design and support model.

Can an HGX-based server from one OEM be serviced by another OEM?

Generally no. Support and warranty terms are tied to the OEM that built and sold the specific HGX-based system, so switching support providers after purchase is uncommon and usually not supported.

Which is faster to deploy, DGX or HGX?

DGX systems are typically faster to deploy since they arrive pre-validated and pre-configured by NVIDIA, while HGX-based systems require OEM integration and testing time that varies by vendor and configuration complexity.

How Nanobase AI helps

Nanobase AI, an accepted member of the NVIDIA Inception Program, helps clients weigh DGX simplicity against HGX flexibility based on their existing infrastructure, procurement relationships, and support requirements, and manages the OEM comparison process when HGX is the better fit. Learn more about our GPU procurement and deployment services.

Ready to discuss your project? Contact Nanobase AI or email hello@bumu.tech.