I'm not in a position to recommend or not a particular provider for gpu-equipped servers, simply because I've never had the need for gpus.
My first thought was related to colocation services. From what I understand, a lot of people avoid on-premise/in-house solutions because they don't want to deal with server rooms, redundant power, redundant networks, etc.
So people go to the cloud and pay horrendous prices there.
Why not take a middle path? Build your own custom server with your perferred hardware and put in a colocation
There are several tier-two clouds that offer GPUs but I think they generally fall prey to the many of the same issues you'll find with AWS. There is a new generation of accelerator native clouds e.g. Paperspace (https://paperspace.com) that cater specifically to HPC, AI, etc. workloads. The main differentiators are:
- much larger GPU catalog
- support for new accelerators e.g. Graphcore IPUs
- different pricing structure that address problematic areas for HPC such as egress
However, one of the most important differences is the lack of unrelated web services related components that pose a major distraction/headache to users that don't have a DevOps background (which AWS obviously caters to). AWS can be incredibly complicated. Simple tasks are encumbered by a whole host of unrelated options/capabilities and the learning curve is very steep. A platform that is specifically designed to serve the scientific computing audience can be much more streamlined and user-friendly for this audience.
Lambda A100s - $1.10 / hr
Paperspace A100s - $3.09 / hr
Genesis A100s - no A100s but their 3090 (1/2 the speed of 100) is - $1.30 / hr for half the speed
And why do people only know Hetzner, OVH and Linode as alternatives to the big cloud providers?
There are so many good and inexpensive server hosting providers, some with decades of experience.