The g5.2xlarge pairs 8 vCPU with 32 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 "2xlarge" 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; g6.2xlarge is the direct replacement at this size, scoring 167,347 CoreMark/s against this instance's 144,424 — roughly 16% 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
g5.2xlarge pairs 1 Ampere GPU (24 GiB VRAM) with 8 vCPU. Spot's GPU node uses the NVIDIA A30 (Ampere, 24 GB VRAM) with 24 vCPU and 64 GiB of memory — more GPU memory, more CPU and newer hardware than g5.2xlarge. For inference, batch transcoding and single-card fine-tuning that is an upgrade rather than a compromise. 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 diskg5.2xlarge comes with 1 × 450 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
Region
AWS on-demand
AWS Spot
1-yr Reserved
3-yr Reserved
Rackspace Spot
You save
US West, San Jose
$0.191
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 32 GiB of RAM
●Jobs that want 1 × 450 GB of local NVMe scratch space
●Network-heavy services — AWS rates this size at Up to 10 Gigabit
Avoid if
●Starting a new deployment. g6.2xlarge is the newer generation at this size.
●The working set needs more than 32 GiB of RAM
●More than 4.00 GiB of RAM per vCPU is needed — that ratio is fixed for the whole family
●Anything the CPU can do fast enough. GPU hours are the most expensive on the price list.
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.
