Instances›AWS EC2›g5›g5.48xlarge
Compute
vCPUs192
Memory768 GiB
Mem / vCPU4.00 GiB
ProcessorEPYC 7R32
Clock speed2.8 GHz
Architecturex86_64
Storage
Type2 × 3,800 GB NVMe SSD
Bandwidth19,000 Mbps
Throughput2375 MB/s
IOPS80,000
Networking
Performance100 Gigabit
Max ENIs7
IPv6Yes
GPUNVIDIA A10G
Family sizes
g5.xlarge4 vCPU · 16 GiB
g5.2xlarge8 vCPU · 32 GiB
g5.4xlarge16 vCPU · 64 GiB
g5.8xlarge32 vCPU · 128 GiB
g5.12xlarge48 vCPU · 192 GiB
g5.16xlarge64 vCPU · 256 GiB
g5.24xlarge96 vCPU · 384 GiB
g5.48xlarge192 vCPU · 768 GiB
g5.48xlarge

The g5.48xlarge pairs 192 vCPU with 768 GiB of RAM, the 4.00 GiB-per-vCPU ratio that marks a GPU instance. In the name, "g" is graphics, "5" is the generation and "48xlarge" is the size within the g5 family. It runs on AMD EPYC 7R32 at 2.8 GHz, and AWS introduced it in November 2021. AWS has since shipped g6 and g7; g6.48xlarge is the direct replacement at this size, scoring 3,842,690 CoreMark/s against this instance's 3,614,458 — roughly 6% more throughput for the same vCPU count. Rackspace Spot has no equivalent to offer: 8 × NVIDIA A10G 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

g5.48xlarge is 8 Ampere, Ampere, Ampere, Ampere, Ampere, Ampere, Ampere, Ampere GPUs (192 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$16.288$5.162$10.261$7.036
US Central, Chicagono AWS region
US Central, Dallasno AWS region
Hong Kong$25.076$15.798$10.833
Sydney, Australia$21.178$21.178$13.342$9.149
London, UK$20.676$20.676$13.026$8.932
US West, San Jose
US Central, Dallas 2no AWS region
US East, N. Virginia 2$16.288$5.162$10.261$7.036
When to use it
Good for
  • ●Model inference and embedding generation
  • ●Video transcoding and image processing
  • ●Machine learning experimentation and fine-tuning
  • ●Workloads that fit inside 768 GiB of RAM
  • ●Jobs that want 2 × 3,800 GB of local NVMe scratch space
  • ●Network-heavy services — AWS rates this size at 100 Gigabit
Avoid if
  • ●Starting a new deployment. g6.48xlarge is the newer generation at this size.
  • ●The working set needs more than 768 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 4.00 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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