Instances›AWS EC2›g7e›g7e.48xlarge
Compute
vCPUs192
Memory2048 GiB
Mem / vCPU10.67 GiB
ProcessorXeon Scalable
Clock speed3.2 GHz
Architecturex86_64
Storage
Type4 × 3,800 GB NVMe SSD
Bandwidth100,000 Mbps
Throughput12500 MB/s
IOPS400,000
Networking
Performance1600 Gigabit
Max ENIs40
IPv6Yes
GPUNVIDIA RTX PRO 6000 Blackwell
Family sizes
g7e.2xlarge8 vCPU · 64 GiB
g7e.4xlarge16 vCPU · 128 GiB
g7e.8xlarge32 vCPU · 256 GiB
g7e.12xlarge48 vCPU · 512 GiB
g7e.24xlarge96 vCPU · 1024 GiB
g7e.48xlarge192 vCPU · 2048 GiB
g7e.48xlarge

The g7e.48xlarge is a GPU AWS EC2 instance: 192 vCPU and 2048 GiB of memory, 10.67 GiB per vCPU. In the name, "g" is graphics, "7" is the generation, "e" marks extended capacity and "48xlarge" is the size within the g7e family. It runs on Intel Xeon Scalable (Emerald Rapids) at 3.2 GHz, and AWS introduced it in January 2026. g7e is the current generation of the g family, so there is no newer AWS size to migrate to. Rackspace Spot has no equivalent to offer: 8 × NVIDIA RTX PRO 6000 Blackwell wired together behind a high-speed interconnect is one tightly coupled machine, not 8 independent nodes — and that interconnect is usually what the instance was bought for. Spot's largest VM tops out at 16 vCPU and 128 GiB, and even that is not the missing piece here. The table below prices what AWS charges; the honest answer on the Spot side is that this workload stays where it is.

Match qualityNo equivalent

g7e.48xlarge is 8 Blackwell, Blackwell, Blackwell, Blackwell, Blackwell, Blackwell, Blackwell, Blackwell GPUs (768 GiB VRAM) wired together inside one chassis. The interconnect is what you bought — that is what makes it one accelerator with pooled memory rather than several machines — and Rackspace Spot has nothing that reproduces it. The Spot GPU class is built on the NVIDIA A30 (Ampere, 24 GB VRAM), and separate nodes of it on ordinary datacentre networking are not a substitute for a single interconnect-joined node.

Split the job across independent single-GPU nodes only if it is data-parallel with no per-step synchronisation and the model fits one card. Model-parallel work, or anything synchronising gradients every step, does not survive the move. Rackspace Spot sells x86_64 Kubernetes nodes up to 16 vCPU, plus one NVIDIA A30 GPU class.

Pricing by region
1 hr
RegionAWS on-demandAWS Spot1-yr Reserved3-yr ReservedRackspace SpotYou save
US East, N. Virginia$33.144$14.082
US Central, Chicagono AWS region
US Central, Dallasno AWS region
Hong Kong
Sydney, Australia
London, UK$57.607$17.311
US West, San Jose
US Central, Dallas 2no AWS region
US East, N. Virginia 2$33.144$14.082
When to use it
Good for
  • ●Video transcoding and image processing
  • ●Machine learning experimentation and fine-tuning
  • ●Remote graphics workstations and rendering
  • ●Workloads that fit inside 2048 GiB of RAM
  • ●Jobs that want 4 × 3,800 GB of local NVMe scratch space
  • ●Network-heavy services — AWS rates this size at 1600 Gigabit
Avoid if
  • ●The working set needs more than 2048 GiB of RAM
  • ●The work is single-threaded. Most of these 192 vCPU would sit idle.
  • ●Anything the CPU can do fast enough. GPU hours are the most expensive on the price list.
  • ●More than 10.67 GiB of RAM per vCPU is needed — that ratio is fixed for the whole family
Rackspace Spot sells spare capacity at market prices. You pay what the market decides, not a list price.
  • Spot sells spare capacity at market prices. It is the cheapest compute on the internet.
  • Prices are set by supply and demand. You pay what the market decides.
  • Compute is delivered as fully managed Kubernetes. All infrastructure is taken care of.
  • Egress costs $0.01/GB after the free allowance. AWS charges $0.09/GB.
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