GPU racks—Bare metal
Direct-attached GPUs with no virtualization overhead and full driver control, measurably faster than virtualized ones.
Full-stack AI. No compromises
- Faster than virtualized~20%
- EdgeLink optics1.6T
- Less for optics than OEMs40%+
- Bandwidth penaltiesNone
From the first run to global serving
Bare-metal GPUs without bandwidth penalties, from training to global inference on one platform.
Your server—Your kernel
Custom kernels, GPU drivers and NUMA-aware tuning, with no hypervisor in the way.
EdgeLink fabric—Up to 1.6T
Optics up to 1.6T built for AI clusters: InfiniBand-compatible, with custom orders the same day.
Bandwidth—No egress fees
Compute-centric pricing, so data-heavy pipelines don’t blow up the bill. Design for performance, not for less traffic.
Inference—Close to users
On demand for experiments, reserved for production: go from development to global serving without switching providers.
Your users—Predictable latency
Serve models close to users worldwide, with predictable latency across regions and one provider to manage.
The same run, five days sooner
Virtualized GPUs run ~15–20% slower. Every step of training pays it, and over a month that is days of cluster time.
The whole cluster is yours: every GPU, switch and link, with nothing between your code and the hardware.
- Training steps since you got here
- Bare metal0
- Virtualized0
- A 30-day cloud run ends on
- Day 25
- Between your code and the GPUs
- Nothing
An illustration: a run that takes 30 days on virtualized GPUs, at bare metal’s ~20% higher throughput. The network and its timing are drawn, not measured.
03The performance gap
The virtualization tax is real
Shared scheduling, abstracted access and egress fees, or bare metal, full control and economics that work.
Bare metalVirtualized cloud
- Hardware
- Bare metal: Bare metal, dedicated
- Virtualized cloud: Virtualized, shared
- Performance
- Bare metal: Full hardware performance
- Virtualized cloud: ~15–20% slower
- Pricing
- Bare metal: Compute-centric
- Virtualized cloud: Egress fees
- Interconnect
- Bare metal: EdgeLink, built in
- Virtualized cloud: Third-party optics
Why AI teams choose bare metal
Cloud GPUs are virtualized and shared, egress fees eat the margin and third-party optics cap the interconnect. We run your models on bare metal, with the network built in.
- ~20%Bare metal
Faster than virtualized
Bare-metal GPUs run ~15–20% faster than virtualized ones: no hypervisor, full driver control.
- 1.6TEdgeLink
The network built in
EdgeLink optics up to 1.6T for AI clusters, 40%+ below the OEMs, with custom orders the same day.
- One stackDedicated AI clusters
From the optics to deployment
One provider from the optics to the compute to deployment, with no bandwidth penalties for data-heavy work.
- At the edgeEdgeAI
Inference close to users
Serve models near your users, not only in central regions, with predictable latency across regions.
Get GPU access