Instances›AWS EC2›g5›g5.8xlarge
Compute
vCPUs32
Memory128 GiB
Mem / vCPU4.00 GiB
ProcessorEPYC 7R32
Clock speed2.8 GHz
Architecturex86_64
Storage
Type1 × 900 GB NVMe SSD
Bandwidth16,000 Mbps
Throughput2000 MB/s
IOPS65,000
Networking
Performance25 Gigabit
Max ENIs8
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
g5.8xlarge

g5.8xlarge is AWS's GPU EC2 size at 32 vCPU and 128 GiB. In the name, "g" is graphics, "5" is the generation and "8xlarge" 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; g6.8xlarge is the direct replacement at this size, scoring 689,915 CoreMark/s against this instance's 621,903 — roughly 11% more throughput for the same vCPU count. Rackspace Spot runs one GPU class, gpu.vs2.xlargeplusplus — a single NVIDIA A30 with 24 vCPU and 64 GiB, in San Jose only. Against this instance's 1 × NVIDIA A10G that is a fair swap for inference and media work — the A30 carries more memory and more throughput per card.

Match qualityComparable GPU

g5.8xlarge pairs 1 Ampere GPU (24 GiB VRAM) with 32 vCPU. Spot's GPU node uses the NVIDIA A30 (Ampere, 24 GB VRAM) with 24 vCPU and 64 GiB of memory — newer hardware with more GPU memory, but 24 vCPU against 32. For inference, batch transcoding and single-card fine-tuning the card is the upgrade; anything CPU-bound running alongside it gets less to work with. The catch is location rather than hardware: US West, San Jose is the only Spot region that offers it, so latency to your users and egress to your data are the things to check.

No local diskg5.8xlarge comes with 1 × 900 GB NVMe SSD attached to the machine. Spot nodes use network storage only, so that disk doesn't come with it. If you were using it as fast scratch space, you'd move to a persistent volume or object storage, which are slower to read.
Pricing by region
1 hr
RegionAWS on-demandAWS Spot1-yr Reserved3-yr ReservedRackspace SpotYou save
US West, San Jose$0.191
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 128 GiB of RAM
  • ●Jobs that want 1 × 900 GB of local NVMe scratch space
  • ●Network-heavy services — AWS rates this size at 25 Gigabit
Avoid if
  • ●Starting a new deployment. g6.8xlarge is the newer generation at this size.
  • ●The working set needs more than 128 GiB of RAM
  • ●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
  • ●The work is single-threaded. Most of these 32 vCPU would sit idle.
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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