Floyo vs RunComfy: Which ComfyUI Cloud Platform Is Right for You?

What is the difference between Floyo and RunComfy?

The difference is architecture. Floyo is serverless: zero machine wait times, you pay only during active generation. RunComfy uses the machine-instance model: pick a GPU, just sit there waiting for machines to start, and pay for the entire session.

This shapes everything about how the two platforms work.

On Floyo, there is no machine to manage. No startup wait time. No idle billing. You browse workflows, click run, and generation starts. Building and editing workflows is free. Your generation is tracked through FloTime. When you are not generating, the meter is off.

On RunComfy, you get a private ComfyUI environment on a dedicated GPU. You pick from seven GPU tiers (T4 through H200), and the machine starts in 3-5 minutes or more(sometimes longer depending on how many nodes are loaded). ComfyUI-Manager is available, though node installation is limited to nodes whose dependencies match what is already on that machine instance. The meter runs the entire time your machine is on. If you spend an hour tweaking a workflow and 10 minutes generating, you pay for 70 minutes.

Serverless is where cloud compute is heading. You see it everywhere: web infrastructure (Lambda, Vercel), AI inference (Replicate, Modal), and now ComfyUI. The machine-instance model where you start a server, pay for idle time, and manage your own environment is the previous generation. Floyo was built from scratch on the assumption that you should never think about machines. RunComfy is still built on the old model.

The trajectory matters if you are choosing a platform to build your workflow library on.

How does team collaboration work on Floyo vs RunComfy?

Floyo is the only ComfyUI cloud platform with real team collaboration. Shared run history, shared files and models, workflow pages for organizing pipelines, and a team usage dashboard. RunComfy has no team features. Each user gets their own machine.

If you work alone, skip this section. If you work with even one other person, it changes everything.

Shared run history: see what your teammates did

Your teammate runs a workflow at 3pm. At 5pm, you open that exact run. Same parameters, same seed, same inputs. You adjust the prompt, hit re-run. No "can you send me your settings?" No screenshots in Slack. No version confusion.

This sounds simple. In practice, it eliminates the most common friction in creative team workflows. When every run is visible and reproducible, your team stops wasting time reconstructing what someone else already figured out.

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

Upload a custom LoRA, and your whole team has it. Same for checkpoints, input files, and outputs. No re-downloading to separate machines. No emailing model links. No one running the wrong version of a LoRA because they grabbed it three weeks ago.

Workflow pages: organize your pipelines

Create private collections of workflows organized by project or client. Document how workflows connect. When someone new joins the team, the knowledge is in the workflow pages, not in someone's head or buried in a Slack thread from four months ago.

Team usage dashboard: one bill, full visibility

Pooled FloTime and storage across the team. Each team member you add increases the pool by 22 hours of FloTime and 200GB of storage (on the Trailblazer plan). One dashboard, one bill. Track who is using what without micromanaging.

RunComfy does let you cloud-save your ComfyUI environment (workflow JSON, nodes, models, Python environment). This saves a snapshot of your machine for your own account so you can resume where you left off. It is not a collaboration tool. There is no shared workspace, no shared asset library, no pooled billing.

Can I install custom nodes on Floyo and RunComfy?

Floyo comes with 300+ custom nodes pre-installed and maintained. New nodes are added regularly, and you can request specific ones, typically added within 48 hours. RunComfy includes ComfyUI-Manager, but node installation has limitations tied to the machine's pre-loaded dependencies.

Floyo's 300+ nodes cover the workflows production teams use: ControlNet, IP-Adapter, AnimateDiff, InstantID, FaceDetailer, and many more. The Floyo team tests compatibility across all pre-installed nodes and handles updates. You never deal with dependency conflicts, broken installs, or version mismatches between packages. New nodes are added every day as the ecosystem evolves.

RunComfy includes ComfyUI-Manager in every environment. You can browse and install nodes from within the interface. However, each workflow card starts a specific machine instance with a specific set of dependencies (CUDA version, Python version, libraries). If a node requires dependencies that are not already on that machine, the installation will fail. This is the same limitation that affects all machine-instance ComfyUI platforms. It works well for nodes that share common dependencies. It breaks for nodes that need different versions of core libraries.

Models, LoRAs, and checkpoints

On Floyo, you can upload your own LoRAs through self-service on all plans, including free. Uploaded LoRAs are shared across your team. For checkpoints and other model types, hundreds of popular models are already preloaded. If you need a checkpoint that is not available, contact Floyo's support team (very responsive) and they will upload it, typically within 48 hours. Self-service checkpoint uploads are coming soon, within weeks.

On RunComfy, you can upload models and LoRAs to your private storage (10GB on pay-as-you-go, 200GB on Pro). You can also download models from Civitai or HuggingFace at 25x faster speeds. Uploads live on your individual machine with no team sharing.

How much does Floyo cost compared to RunComfy?

Floyo charges for generation time. RunComfy charges for machine time. That single difference matters more than any rate on either pricing page.

Most of your time in ComfyUI is not generating. It is building nodes, writing prompts, adjusting parameters, reviewing outputs. On Floyo, all of that is free. On RunComfy, the meter runs the entire session.

Solo user example

10 hours per week in ComfyUI, about 2 hours of actual generation. Floyo Pathfinder ($35/mo) gives you 10 hours of generation time, which covers it (Floyo uses H100s so it's way more powerful). RunComfy at $1.75/hr (A10G) for 40 hours of machine time costs $70/mo. Same creative output. Half the price on Floyo.

Team example

A team of 3 on Floyo Trailblazer: $70/mo per user = $210/mo total. The team gets 66 hours of pooled FloTime (22 hrs x 3 members). On RunComfy, 3 people each using 10 hrs/week of machine time at $1.75/hr: $210/mo. Similar total cost, but on Floyo only generation time counts. The team's 66 pooled hours of generation time goes much further than 120 hours of machine time where most of it is idle.

Read more: Full pricing details for both platforms ▼

Does Floyo or RunComfy support LoRA training?

Both platforms support dedicated LoRA training. Floyo trains on H100 NVL GPUs with your trained LoRAs automatically shared across your team. RunComfy offers a dedicated Trainer product with discounted GPU rates and persistent checkpoints.

On Floyo, you train LoRAs on the same H100 NVL hardware that runs your workflows. Your trained LoRAs are immediately available to your entire team. No exporting, no re-uploading, no version confusion. Train once, everyone uses it.

RunComfy's Trainer has dedicated pricing ($4.49/hr for H100 training vs. $7.49/hr for inference), auto-release when training finishes, and persistent checkpoints for pause-and-resume. If you do high-volume training and want the lowest per-hour rate, these features matter. But trained LoRAs live on your individual machine. Sharing with teammates means manual file transfer.

Can I deploy ComfyUI workflows as an API on Floyo or RunComfy?

RunComfy offers API deployment today. Any cloud-saved workflow can become an endpoint with autoscaling. Floyo's API is coming soon and will be truly serverless.

RunComfy's API deploys from a saved workflow with no additional code. It supports autoscaling, versioned deployments, and real-time monitoring. If you need ComfyUI workflows integrated into production applications today, RunComfy has this capability.

One important caveat: RunComfy's API billing is still based on machine time, not per-call. Their docs show that if you set minimum instances above zero, you pay for full uptime including idle time between API calls. On-demand instances scale up with demand but still bill for the full duration they are running. This is closer to a managed GPU endpoint than a truly pay-per-invocation serverless API.

Floyo's API is in development. It will follow the same serverless architecture as the rest of the platform: pay only when your workflow is generating, not for idle time between calls. If API access is a hard requirement right now, RunComfy is the option. If you can wait, Floyo's approach will be more cost-efficient for variable workloads.

Does Floyo or RunComfy have better GPU hardware?

Floyo runs everything on H100 NVL GPUs: 94GB VRAM and 3.9 TB/s memory bandwidth. Premium hardware for every workflow, no GPU selection, no guessing. RunComfy offers seven tiers from T4 (16GB) to H200 (141GB), and you choose which one fits your budget.

For heavy open-source video workflows (Wan 2.2, HunyuanVideo), memory bandwidth is the bottleneck. The H100 NVL's 3.9 TB/s keeps large video models running fast. You never think about whether your card has enough VRAM or whether you picked the right tier. Every workflow gets the same hardware.

RunComfy gives you more GPU options. A T4 at $0.99/hr works for simple image generation. An H200 at $8.75/hr gives you 141GB for extremely large models. The tradeoff: you have to know which tier your workflow needs, and a wrong choice means wasted time or a failed run.

Both platforms also support closed-source models (Kling, Seedance, Sora, Flux Kontext Pro) through API calls at per-generation pricing. These do not depend on GPU hardware and cost extra on both platforms.

What if I create workflows and want to share or sell them?

Floyo has a creator economy. Publish workflows, build a creator page, organize collections, add password protection for Patreon or Gumroad, track analytics. RunComfy has no creator tools and no way for users to publish workflows.

On Floyo, workflow creators are first-class. Publish a workflow, people discover it through search and curated categories, track performance through analytics. Password protection lets you gate premium workflows behind existing memberships. Build collections to organize your work by theme, style, or use case.

RunComfy's 200+ workflows are curated by the RunComfy team. Each workflow card is a pre-configured machine instance with specific nodes and dependencies loaded. There is no community publishing, no creator profiles, no monetization. If you build workflows and want people to find and use them, Floyo is the only platform designed for it.

Should I use Floyo or RunComfy for my ComfyUI workflows?

For teams, creators, and users who want instant workflows with predictable pricing: Floyo. For solo users who want a full ComfyUI machine environment with API deployment today: RunComfy.

Read more: Recommendations for specific use cases ▼

Floyo vs RunComfy: quick reference

Feature	Floyo	RunComfy
Architecture	Serverless. Instant start. Pay per generation.	Machine-instance. Pick GPU, machine wait time (3-5 min), pay for building and iterating also.
Team collaboration	Shared runs, assets, workflow pages, dashboard, pooled billing.	None. Individual machines only.
Custom nodes	300+ managed, new nodes added daily. Request new (48hr).	ComfyUI-Manager included. Installation limited by machine dependencies.
LoRA uploads	Self-service, all plans, team shared.	Self-service, individual storage only.
Checkpoint uploads	Hundreds preloaded. Request support for others. Self-service coming soon.	Upload from Civitai/HuggingFace at 25x speed.
LoRA training	On H100 NVL. Team shared.	Dedicated Trainer. Lower rates ($4.49/hr H100).
API	Coming soon (truly serverless).	Live. Autoscaling, but billed per-hour machine time.
GPU	H100 NVL (94GB, 3.9 TB/s). One tier.	T4 to H200 (16-141GB). 7 tiers.
Closed-source models	API Wallet. Per-run pricing shown before generation.	Models product. Per-generation (Kling, Sora, Wan 2.5, etc.).
Free tier	20 min/day.	Free account, no free GPU time.
Pricing	$15-$70/mo per user. Generation time included.	$0.99-$8.75/hr machine time. Pro: $29.99/mo for discounts.
Creator tools	Pages, collections, analytics, password gating.	None.

Frequently asked questions about Floyo vs RunComfy

Is Floyo or RunComfy better for my needs?

Floyo is the more complete platform. Serverless architecture, team collaboration, creator economy, LoRA training with team sharing, 300+ managed nodes, H100 hardware, and a free tier. RunComfy's main advantages are a full ComfyUI machine environment, a wider range of GPU tiers, and API deployment today (billed per-hour).

If you work with a team, Floyo is the only real option. No other cloud ComfyUI platform has shared run history, shared assets, or pooled billing. If you work solo and want a machine you control with API access today, RunComfy provides that.

Floyo has a free tier with 20 minutes per day. Try it and see how zero-wait serverless feels compared to managing a machine.

Try Floyo Free → View Pricing