Floyo vs Comfy Cloud: Which ComfyUI Platform Should Your Team Use?

A detailed comparison for creative teams evaluating cloud ComfyUI platforms for production work. Covers collaboration, custom node support, and real-world workflow requirements.

What is the difference between Floyo and Comfy Cloud?

Floyo is a workflow platform built for teams. Comfy Cloud is cloud compute for individual users. That is the core divide, and it shapes everything else.

Both let you run ComfyUI in a browser without installing anything locally. Both give you access to powerful GPUs. But they are built for different users with different needs.

Floyo comes from ThinkDiffusion, a team that has been running cloud GPU infrastructure for years. They built it around a specific insight: the hard part of ComfyUI is not running workflows. It is sharing them, collaborating on them, and managing them across a team. So that is what they focused on.

Comfy Cloud comes from Comfy Org, the team that maintains the main branch of the open source ComfyUI repo. But their platform is early-stage, with limited node support and no team features. It is cloud compute with a familiar face.

Here is where that difference shows up in practice:

The rest of this comparison digs into what these differences mean for your work.

Which platform should I use for a production project with multiple team members?

For any project involving more than one person, Floyo is the only viable choice right now. Comfy Cloud has no team features. You cannot invite a teammate.

This is not a minor gap. Team collaboration is Floyo reason for existing. They watched studios and agencies struggle with the same problems over and over: artists emailing JSON files, hunting for missing assets, trying to recreate each other results from memory. So they built a platform where that friction disappears.

Here is what team collaboration looks like on Floyo:

Shared run history: see what your teammates did

Every time someone on your team runs a workflow, Floyo captures the full context. Not just the output, but the exact parameters, the input files, the LoRAs, everything. You can open any teammate run and see precisely what they did.

This solves one of the most frustrating problems in creative collaboration: the "can you send me your settings?" loop. Someone generates something great. You want to iterate on it. So you ask: "What seed did you use? What CFG? What was your denoise strength?" And they do not remember. Or they do remember, but they forgot which LoRA they had loaded. Or they used an input image that is now buried in their downloads folder.

On Floyo, you skip all of that. You open their run. You see everything. You can re-run it as they did, or adjust a parameter and see what changes. The entire handoff happens in seconds instead of a back-and-forth that drags across Slack messages and email attachments.

For animation and video projects, this is particularly critical. When you are iterating on a 30-second sequence and each render takes longer than a coffee break, you cannot afford to lose track of what combination of settings produced that one good result three days ago.

Shared files, models, and LoRAs: upload once, everyone uses it

In a typical team workflow, someone finds a useful LoRA, downloads it, uploads it to the platform, and starts using it. On Comfy Cloud (or any individual-focused platform), that LoRA exists only in their account. If a teammate wants to use it, they need to find it, download it, upload it themselves.

On Floyo, uploaded assets are shared across the team. One person uploads the LoRA, and everyone can use it immediately. Same with input images, reference videos, custom checkpoints. Anything that goes into your workflows.

This sounds like a small thing until you are managing a production with hundreds of custom assets across multiple artists. The alternative is chaos: duplicate uploads, version confusion, storage costs multiplied by team size, and constant "hey can you send me that file?" interruptions.

Workflow pages: organize your pipelines in one place

Most production projects do not use one workflow. They use many. Maybe you have a character consistency pipeline, a background generation workflow, and a compositing process. Each one involves different settings, different models, different input requirements.

Floyo lets you create workflow pages that organize these pipelines. Think of it as a private wiki for your team AI workflows. Each page can contain multiple related workflows, documentation about when to use them, notes on what parameters to adjust for different scenarios, and links to the specific assets each workflow needs.

This matters because institutional knowledge otherwise disappears. Someone figures out the perfect settings for generating consistent characters. They leave, or forget. Without documentation, the next person has to rediscover everything from scratch. Workflow pages make that knowledge persistent and shareable.

This also matters for teams with mixed skill levels. Your senior artists can build workflows and publish them to private team pages, complete with documentation and parameter guides. Beginners open the page, adjust inputs, and run. No ComfyUI expertise required to start producing.

Full team usage view: track who is using what

For team leads and producers, visibility into resource usage matters. Floyo provides a centralized dashboard where you can see which team members are running workflows, how much GPU time each person is using, and what the overall team consumption looks like.

This is not about surveillance. It is about planning. If you are managing a budget or trying to forecast costs, you need to understand usage patterns. If one artist is burning through GPU hours because they are rendering tests inefficiently, you want to know that before the invoice arrives.

The team pool model also simplifies billing. Instead of managing individual subscriptions for each artist, you have pooled FloTime that the whole team draws from. One invoice, one set of resources, centralized management.