Instances›AWS EC2›trn1n›trn1n.32xlarge
Compute
vCPUs128
Memory512 GiB
Mem / vCPU4.00 GiB
ProcessorXeon Scalable
Clock speed3.5 GHz
Architecturex86_64
Storage
Type4 × 1,900 GB NVMe SSD
Bandwidth80,000 Mbps
Throughput10000 MB/s
IOPS260,000
Networking
Performance16x 100 Gigabit
Max ENIs80
IPv6Yes
GPUNone
Family sizes
trn1n.32xlarge128 vCPU · 512 GiB
trn1n.32xlarge

trn1n.32xlarge is AWS's machine-learning accelerator EC2 size at 128 vCPU and 512 GiB. In the name, "trn" is Trainium, AWS's training silicon, "1" is the generation, "n" marks enhanced networking and "32xlarge" is the size within the trn1n family. It runs on Intel Xeon Scalable (Icelake) at 3.5 GHz, and AWS introduced it in April 2023. AWS has since shipped trn2. Rackspace Spot has no equivalent to offer: the Inferentia and Trainium accelerators are AWS-exclusive silicon with no third-party equivalent. 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

trn1n.32xlarge is Machine Learning ASIC hardware. That accelerator has no counterpart in the Rackspace Spot catalog, and nothing in it emulates one at a speed worth paying for — this is a genuine no-match, not a weak one.

Rackspace Spot sells x86_64 Kubernetes nodes up to 16 vCPU, plus one NVIDIA A30 GPU class. What does move is the CPU half of the pipeline built around the accelerator: ingest, pre- and post-processing, orchestration, and the serving front end. On most accelerator workloads that tier runs continuously while the accelerator itself is duty-cycled, which is where the bill actually accumulates.

Pricing by region
1 hr
RegionAWS on-demandAWS Spot1-yr Reserved3-yr ReservedRackspace SpotYou save
US East, N. Virginia$24.780$6.761$15.247$9.287
US Central, Chicagono AWS region
US Central, Dallasno AWS region
Hong Kong
Sydney, Australia
London, UK
US West, San Jose
US Central, Dallas 2no AWS region
US East, N. Virginia 2$24.780$6.761$15.247$9.287
When to use it
Good for
  • ●Cost-per-inference optimisation inside AWS
  • ●Inference or training on AWS's own accelerator silicon
  • ●Workloads already built against the Neuron SDK
  • ●Workloads that fit inside 512 GiB of RAM
  • ●Jobs that want 4 × 1,900 GB of local NVMe scratch space
  • ●Network-heavy services — AWS rates this size at 16x 100 Gigabit
Avoid if
  • ●The working set needs more than 512 GiB of RAM
  • ●The work is single-threaded. Most of these 128 vCPU would sit idle.
  • ●GPU or FPGA acceleration is needed
  • ●Frameworks that have not been compiled for the Neuron SDK.
  • ●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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