g6f.4xlarge is AWS's GPU EC2 size at 16 vCPU and 64 GiB. In the name, "g" is graphics, "6" is the generation and "4xlarge" is the size within the g6f family. It runs on AMD EPYC 7R13 Processor at 2.6 GHz, and AWS introduced it in July 2025. AWS has since shipped g7; g7.4xlarge is the direct replacement at this size, scoring 540,358 CoreMark/s against this instance's 348,755 — roughly 55% 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 0.5 × NVIDIA L4 that is a fair swap for inference and media work — the A30 carries more memory and more throughput per card.
Match qualityComparable GPU
g6f.4xlarge pairs 0.5 GPUs (12 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 g6f.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 diskg6f.4xlarge 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
●Machine learning experimentation and fine-tuning
●Remote graphics workstations and rendering
●CUDA-accelerated batch jobs
●Workloads that fit inside 64 GiB of RAM
●Jobs that want 1 × 450 GB of local NVMe scratch space
●Network-heavy services — AWS rates this size at Up to 25 Gigabit
Avoid if
●The working set needs more than 64 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 16 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.
