Instances›AWS EC2›g6›g6.48xlarge
Compute
vCPUs192
Memory768 GiB
Mem / vCPU4.00 GiB
ProcessorEPYC 7R13 Processor
Clock speed2.6 GHz
Architecturex86_64
Storage
Type8 × 940 GB NVMe SSD
Bandwidth60,000 Mbps
Throughput7500 MB/s
IOPS240,000
Networking
Performance100 Gigabit
Max ENIs15
IPv6Yes
GPUNVIDIA L4
Family sizes
g6.xlarge4 vCPU · 16 GiB
g6.2xlarge8 vCPU · 32 GiB
g6.4xlarge16 vCPU · 64 GiB
g6.8xlarge32 vCPU · 128 GiB
g6.12xlarge48 vCPU · 192 GiB
g6.16xlarge64 vCPU · 256 GiB
g6.24xlarge96 vCPU · 384 GiB
g6.48xlarge192 vCPU · 768 GiB
g6.48xlarge

The g6.48xlarge 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, "6" is the generation and "48xlarge" is the size within the g6 family. It runs on AMD EPYC 7R13 Processor at 2.6 GHz, and AWS introduced it in April 2024. AWS has since shipped g7; g7.48xlarge is the direct replacement at this size, scoring 5,701,982 CoreMark/s against this instance's 3,842,690 — roughly 48% more throughput for the same vCPU count. Rackspace Spot has no equivalent to offer: 8 × NVIDIA L4 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

g6.48xlarge is 8 Ada Lovelace, Ada Lovelace, Ada Lovelace, Ada Lovelace, Ada Lovelace, Ada Lovelace, Ada Lovelace, Ada Lovelace 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$13.350$3.362$8.691$6.128
US Central, Chicagono AWS region
US Central, Dallasno AWS region
Hong Kong
Sydney, Australia$17.358$2.113$11.300$7.967
London, UK$16.947$4.666$11.032$7.779
US West, San Jose
US Central, Dallas 2no AWS region
US East, N. Virginia 2$13.350$3.362$8.691$6.128
When to use it
Good for
  • ●Machine learning experimentation and fine-tuning
  • ●Remote graphics workstations and rendering
  • ●CUDA-accelerated batch jobs
  • ●Workloads that fit inside 768 GiB of RAM
  • ●Jobs that want 8 × 940 GB of local NVMe scratch space
  • ●Network-heavy services — AWS rates this size at 100 Gigabit
Avoid if
  • ●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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