There's a middle way: qblocks.cloud - This platform that enables access of unused GPU servers across the globe. It works like a traditional cloud by offering scalability, security and reliability while being upto 80% low cost for AI workloads. Also, offers inbuilt Jupyterlab, AI framework, GPU driver support out of the box. Thus no time wasted in server setup. Source: over 1 year ago

Golem, develop Docker applications and make use of their (now) very limited features. It's best suited for heavy calculations, or calculations you can split up between dozens or hundreds of nodes through sharding. A fork is working on bringing GPU & internet access, but it can be hard otherwise. They have a GLM Rewards Program that - generously rewards up to 20 users per month under regular conditions. Source: almost 2 years ago

For compute, my experience has been the best with Akash, then Golem, then I have been unsuccessful with any other project as of yet. Both of these supports Docker images, but Golem is painfully thorough with securing providers with sandboxing in both networking and workloads. This makes Akash easier to use right now when wanting to run something more advanced such as a custom backend or a Minecraft Server. Source: almost 2 years ago

If you want to run scientific calculations or similar, I highly recommend Golem. Right now, its best applications are ones that can scale by sharding, to use parallel computations. Think doing 100 similar small jobs on 100 computers instead of 1 large job on 1 computer. One average CPU-month costs $3.17, or you can rent 100 CPU-hours for $0.44. Notable examples are blender_cuda which runs on a GPU, and the... Source: almost 2 years ago

If you're not using your computer, you can consider letting other people use it! Come checkout golem, a distributed super computer similar to Folding@Home, but for all kinds of computation not just protein research. You even earn some money and it's really easy to get started. Source: over 2 years ago

This is where the math of VPS on demand for testing vs home starts to matter. OR higher buy in but lower ongoing is SBC boards. Raspberry pi, turingpi, ION whatever boards from nvidia. All have higher cost, more limited abilities (in some ways) but FOR SURE are way lower power/heat than traditional low initial cost/higher ongoing. It's a common issue. Getting yourself a NAS or ESOS or SAN or whatever as an always... Source: over 2 years ago