I ran into this exact issue about 2 years ago about build vs rent. Ultimately I chose build. Here's my thoughts/background: Background: Doing small scale trai

I ran into this exact issue about 2 years ago about build vs rent. Ultimately I chose build. Here's my thoughts/background: Background: Doing small scale training/fine tuning on datasets. Small time commercial applications. I find renting top shelf VM/GPU combos on the cloud to be psychologically draining. Did I forget to shut off my $5 dollar an hour VM during my weekend camping trip? I hate it when I ask myself questions like that. I would rather spend the $2k upfront and ride the depreciation curve, than have the "constant" VM stress. Keep in mind, this is for a single instance, personal/commercial use rig. I feel that DL compute decisions aren't black/white and should be approached in stages. Stage 0: If you do full time computer work at a constant location, you should try to own a fast computing rig. DL or not. Having a brutally quick computer makes doing work much less fatiguing.Plus it opens up the window to experimenting with CAD/CAE/VFX/Photogrammetry/video editing. (4.5ghz i7 8700k +32gb ram +SSD) Stage 1: Get a single 11/12 gb GPU. 1080TI or TitanX (Some models straight up won't fit on smaller cards). Now you can go on Github and play with random models and not feel guilty about spending money on a VM for it. Stage 2: Get a 2nd GPU. Makes for writing/debugging multi-gpu code much easier/smoother. Stage 3: If you need more than 2 GPU's for compute, write/debug the code locally on your 2 GPU rig. Then beam it up to the cloud for 2+ gpu training. Use preemptible instances if possible for cost reasons. Stage 4: You notice your cloud bill is getting pretty high($1k+ month) and you never need more than 8x GPUs for anything that your doing. Start the build for your DL runbox #2. SSH/Container workloads only. No GUI, no local dev. Basically server grade hardware with 8x GPUS. Stage 5: I'm not sure, don't listen to me :)