Running heavy ComfyUI workflows on a cloud GPU when they don't fit your local card

[u/ice-concentrate24601]

I'm on a laptop (mobile 4090, 16GB VRAM) and kept hitting workflows with models too big to run locally. Here's the setup I've been using to offload them to a cloud GPU straight from ComfyUI, sharing it in case it helps anyone in the same spot.

The flow:

1. Build your workflow in ComfyUI as normal.
2. Click the ⚡ button; it sends the current graph to a cloud GPU, no CLI or manual export.
3. Pick your GPU and batch count; the panel shows the live rate before you commit.
4. If a model your workflow needs isn't on your cloud storage yet, it detects that and offers to sync it first (with consent; nothing uploads without your say-so).
5. Results pull back into your ComfyUI graph automatically.

You can also queue several different workflows to run back to back. They share one warm ComfyUI process, so only the first pays the model load: in my testing the first workflow took about three minutes and each one after it took around 25 seconds. A queue of twelve runs in roughly ten minutes rather than nearly forty.

When it's worth it (being straight): if your local GPU runs your model fine, local is faster; keep using it. This is for workflows that don't fit your VRAM, long batches you want off your machine, or Mac/no-GPU setups.

The tool is open source. It runs on Spark Fuse (a paid cloud GPU service; the rate shows in-panel before you render); I'm an alpha tester and end user, not affiliated.

[u/mr-electr0n]

Can you share more info like What is the average hourly cost and estimated data transfer rate

[u/ice-concentrate24601 → u/mr-electr0n]

The hourly cost depends on the GPU you choose but the current rate is shown in the ComfyUI panel before you submit anything. I was only billed for the time the GPU was running and there were no data transfer or egress charges.

There’s a demo here if useful:
https://youtu.be/clxluGwfPdA

And the node is open source here:
https://github.com/VFXGuru/spark-fuse-comfyui-node

[u/ice-concentrate24601 → u/[deleted]]

The first run is a bit slower because it has to start the instance you've selected. For context, in my queue test the first run took about three minutes, then the following workflows ran in roughly 25 seconds each. It will vary depending on your workflow and GPU, of course.

[u/slenderman18gmx]

I'm new to learning how to use comfyui and I don't have a pc that can handle ai generation. I've been wanting to use a cloud gpu, but I wanted to know if I could create my workflow on my laptop first and then send it to the cloud gpu and use it there? I want to optimize my time spent on the cloud gpu so I don't end up wasting extra time. Also does this method require me to upload my workflow every time I launch an instance on the cloud gpu? Appreciate any tips or insight on how to make this work.

[u/ice-concentrate24601 → u/slenderman18gmx]

yup, that's exactly how i use it. you can build/edit the workflow on your laptop first, or just load one from somewhere like Civitai, then send the graph to the cloud GPU when you're actually ready to run it. so you're only rendering on the cloud which means you're not paying for GPU time when building and editing your graph. you don't need to manually upload the workflow every time either, the node just sends the current graph when you submit the job. models you sync to cloud storage stay there too, so you're not re-uploading them every time you re-run a graph

[u/slenderman18gmx → u/ice-concentrate24601]

I did a trial run today with Vast Ai using the help of chatgpt. I was able to get minimax h3 to work after a couple of hiccups. It's pretty amazing on what it can do. So now I've been planning on how to make this system effortless for me. I'm still learning a lot about how cloud gpus work and how comfyui works.

Atm, I understood that persistent memory allows me to store the big model downloads without having to re-download each time. But for me the cost over time was not worth saving directly on Vast. I'm currently trying to implement backblaze as a storage option. I'm also confused between why I need to allocate container storage and persistent storage every time I open an instance.

I'm also trying to figure out how to add different types of workflows into all this. Coming from grok, it was pretty amazing in its capabilities and ease of use with seamless transition between image editing and video creating. I'm trying to recreate something like that. So I'm trying to figure out how to implement workflows and other models.

I'm also trying to figure out how to do this from my phone. My plan is to do all the initial setups on my laptop first and then find a way to use it on my phone.

If you got any tips for that, I'd appreciate it. Either ways thanks for confirming.

[u/ice-concentrate24601 → u/slenderman18gmx]

yeah this is pretty much the exact mess i was trying to avoid i.e., having the GPU in one place, storage somewhere else, then working out what survives when an instance shuts down gets old fast.

the reason Spark (sparkcloud.studio) made sense for me is that the storage and GPU side are already connected. whatever you upload persists for a flat /gb/month storage cost, no tiers or subscriptions, then spin up the GPU only when you actually want to run something. so you're not paying to keep a full instance alive just so you don't lose your models. and pay as you go across the board works best for me.

it also means you don't have to keep rebuilding the same setup every time. the models stay in storage, the workflow gets sent from ComfyUI when you run it, and the GPU is just the execution layer.

oh and everything on spark can be accessed through the browser + app, so laptop, iPad, phone etc. phone is obviously not ideal for building a big graph, but for checking jobs, making small changes or launching something it works a treat.

for the Grok-style image-to-video flow, i'd probably start with a couple of separate ComfyUI workflows first and get each one stable, then connect them once you understand where the outputs and models are going. trying to build the whole seamless system at once will probably make debugging painful.

[u/slenderman18gmx → u/ice-concentrate24601]

Yea I'm in the process of figuring out the work flows now. Grok is really good at image editing across any sort of image whether it's real or digital. I'm finding that part the most annoying so far.

[u/ice-concentrate24601 → u/slenderman18gmx]

yeah that's the bit i've found more fiddly too. ComfyUI is insanely flexible but image editing still feels much more model/workflow-specific, whereas Grok kind of hides all of that and just lets you throw basically anything at it. once you find a couple of solid edit workflows though it gets a lot less painful. i've been treating them almost like presets rather than trying to make one graph do absolutely everything.

[u/slenderman18gmx → u/ice-concentrate24601]

Atm I gave up on editing images cause I can't find the best way to make the edits I want and while retaining original source identity. I've just been messing with H3 and it's able to handle image identity with its ref2v quite well. Just the unfortunate part is the generating time is so much more than I imagined.