The g4dn.4xlarge pairs 16 vCPU with 64 GiB of RAM, the 4.00 GiB-per-vCPU ratio that marks a GPU instance. In the name, "g" is graphics, "4" is the generation, "dn" marks local NVMe storage and enhanced networking and "4xlarge" is the size within the g4dn family. It runs on Intel Xeon Family at 2.5 GHz, and AWS introduced it in September 2019. AWS has since shipped g5, g6 and g7; g5.4xlarge is the direct replacement at this size, scoring 312,480 CoreMark/s against this instance's 230,991 — roughly 35% 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 T4 Tensor Core that is a fair swap for inference and media work — the A30 carries more memory and more throughput per card — and it prices about 87% below the US West (N. California) on-demand rate.
Match qualityComparable GPU
g4dn.4xlarge pairs 1 Turing GPU (16 GiB VRAM) with 16 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 g4dn.4xlarge. 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 diskg4dn.4xlarge comes with 1 × 225 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.
