Instances›AWS EC2›g6›g6.16xlarge
Compute
vCPUs64
Memory256 GiB
Mem / vCPU4.00 GiB
ProcessorEPYC 7R13 Processor
Clock speed2.6 GHz
Architecturex86_64
Storage
Type2 × 940 GB NVMe SSD
Bandwidth20,000 Mbps
Throughput2500 MB/s
IOPS80,000
Networking
Performance25 Gigabit
Max ENIs15
IPv6Yes
GPUNVIDIA L4
Family sizes
g6.xlarge4 vCPU · 16 GiB
g6.2xlarge8 vCPU · 32 GiB
g6.4xlarge16 vCPU · 64 GiB
g6.8xlarge32 vCPU · 128 GiB
g6.12xlarge48 vCPU · 192 GiB
g6.16xlarge64 vCPU · 256 GiB
g6.24xlarge96 vCPU · 384 GiB
g6.48xlarge192 vCPU · 768 GiB
g6.16xlarge

The g6.16xlarge pairs 64 vCPU with 256 GiB of RAM, the 4.00 GiB-per-vCPU ratio that marks a GPU instance. In the name, "g" is graphics, "6" is the generation and "16xlarge" is the size within the g6 family. It runs on AMD EPYC 7R13 Processor at 2.6 GHz, and AWS introduced it in April 2024. AWS has since shipped g7. 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 L4 that is a fair swap for inference and media work — the A30 carries more memory and more throughput per card.

Match qualityComparable GPU

g6.16xlarge pairs 1 Ada Lovelace GPU (24 GiB VRAM) with 64 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 64. 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 diskg6.16xlarge comes with 2 × 940 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
  • ●Video transcoding and image processing
  • ●Machine learning experimentation and fine-tuning
  • ●Remote graphics workstations and rendering
  • ●Workloads that fit inside 256 GiB of RAM
  • ●Jobs that want 2 × 940 GB of local NVMe scratch space
  • ●Network-heavy services — AWS rates this size at 25 Gigabit
Avoid if
  • ●The working set needs more than 256 GiB of RAM
  • ●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 64 vCPU would sit idle.
  • ●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.
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