Floyo
Floyo
Workflows
API
Pricing
Floyo
Floyo
Workflows
API
Pricing

Last updated: July 2026. We tested both platforms using WAN 2.2 video workflows, Flux image workflows, and custom node-heavy pipelines. Pricing verified from official sources. · Floyo Pricing · RunComfy Pricing

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

Floyo and RunComfy are both ComfyUI cloud platforms that let you run ComfyUI online without a local GPU. This comparison covers architecture, team collaboration, ComfyUI API access, GPU tiers, and pricing. The differences start to matter when you need ComfyUI for teams, predictable billing, API deployment, or enterprise controls.

TLDR Floyo is serverless and built for teams. You pay only for generation seconds, workflows start instantly, and your team shares runs, files, and models in one workspace. Starts at $12/month with a free trial.

RunComfy gives you a full ComfyUI machine. You pick your GPU tier, manage your own environment, and pay for the session. No monthly commitment. Starts at $0.99/hour.

Both have live API access. Choose Floyo for collaboration and predictable billing. Choose RunComfy for environment control and GPU flexibility.

Quick verdict

Category Winner Why
ArchitectureFloyoServerless, no idle billing
Team collaborationFloyoOnly option with team features
Custom node breadthFloyoHundreds managed vs self-install
API accessTieBoth live, serverless, auto-scaling
Enterprise controlsFloyoModel gating, audit trail
GPU selectionRunComfy8 tiers, T4 through H200
VRAM ceilingRunComfy141GB (H200) vs 94GB (H100)
Pay-as-you-go flexibilityRunComfyNo monthly commitment needed
LoRA training ratesRunComfyDedicated Trainer, $4.49/hr H100
Pricing (entry)Floyo ($12/mo)Predictable monthly cost + free trial
Creator/monetization toolsFloyoCreator Page, analytics, gating
Content ecosystemRunComfyStronger guides, tutorials, node docs

How do Floyo and RunComfy compare on features?

Feature Floyo RunComfy
ArchitectureServerless. Instant start, pay only for active generation seconds.Machine-instance. Select GPU, wait 3-5 min for startup, pay for full session.
Team collaborationShared run history, shared files/models, workflow pages, team dashboard, pooled resourcesNot available. Individual machines only.
Custom nodesHundreds pre-installed. New nodes within 24h. Enterprise node enforcement per workspace.ComfyUI-Manager for self-install. Depends on machine environment and dependencies.
API access UpdatedFloyo API: any workflow becomes an HTTP endpoint. Auto-scaling, 100 req/min, pay-per-generation.Serverless API with auto-scaling. Deploy from Cloud Save. GPU tier selection. Pay per second.
Access control NewModel gating, permissions, user management, audit trailNot available
Free tier15 min free generation time, no credit cardFree account, no GPU time included
Starting price$12/mo (Explorer, 3.5h)$0.99/hr (T4/A4000, pay-as-you-go)
GPU hardwareNVIDIA H100 NVL, 94GB VRAM8 tiers: T4 (16GB) through H200 (141GB)
LoRA uploadsAll plans. Shared across team.Self-service. Individual machine storage.
LoRA trainingOn-platform, H100 NVL. Trained LoRAs shared team-wide.Dedicated Trainer product. H100 at $4.49/hr, H200 at $5.75/hr.
Concurrent runsUp to 8 per memberOne machine at a time (multiple machines possible)
Creator toolsCreator Page, collections, password gating, analyticsNot available
Workflow sharingShared workflows via link. Recipient clicks Run, same environment.Export JSON or share Cloud Save. Recipient needs own machine.
Commercial useTrust Center: commercial-use warranty, model verificationCheck terms. No public verification program.
Idle billingNo. Pay only for active generation.Yes. Full machine session billed including idle time.

What is the difference between Floyo and RunComfy?

TLDR Floyo is serverless: instant starts, pay only for generation seconds. RunComfy is machine-instance: select a GPU tier, wait for startup, pay for the full session including idle time.

Floyo is a serverless ComfyUI cloud platform. You open a workflow and click Run. No GPU to select, no machine to boot, no idle billing. You pay only for the seconds the GPU is actively processing. Building workflows, adjusting prompts, reviewing outputs: all free.

RunComfy is a machine-instance ComfyUI cloud platform. You select a GPU tier (T4 through H200), start a machine, wait 3-5 minutes for boot, and work inside a full ComfyUI environment. You pay for the entire session. When you are done, you stop the machine.

Most ComfyUI time is not generation time. Building node graphs, writing prompts, downloading models, reviewing outputs: 70-90% of a typical session is non-generation work. On Floyo, that time is free. On RunComfy, you are paying for it.

Real scenario: 2-hour ComfyUI session, 25 minutes of actual generation On Floyo (Pathfinder plan): You use 25 minutes of your 10-hour monthly FloTime allocation. The remaining 1 hour 35 minutes of building and reviewing costs nothing. Effective cost: roughly $1.94 of your monthly plan.

On RunComfy (A6000): You pay for the full 2 hours at $2.50/hr = $5.00. The 1 hour 35 minutes of non-generation time costs you $3.96 in idle billing.
Honest note RunComfy's machine-instance model has a real advantage: you get a full, unrestricted ComfyUI environment. You can install any node via ComfyUI-Manager, configure the environment however you want, and work exactly like you would on a local machine. Some advanced users prefer this level of control. The trade-off is idle billing and startup wait time.

Which ComfyUI cloud platform is best for teams?

TLDR Floyo. It is the only ComfyUI cloud platform with team collaboration: shared runs, shared assets, workflow pages, and a team dashboard. RunComfy has no team features.

Floyo is the only ComfyUI cloud platform built for teams. RunComfy has no team features: each user operates an isolated machine with individual storage. There is no way to invite a teammate or share assets within a workspace.

The core idea: expertise compounds. The people with the most skill pick and configure the right workflows, set them for the team, and everyone else runs them reliably. One expert's judgment scales to the whole team. That only works if the platform supports it.

Floyo's collaborative workspace covers four areas:

  • Shared run history. Every team member's runs are visible: parameters, inputs, LoRAs, outputs. Open a teammate's run, adjust a setting, re-run. No more "can you send me your settings?" over Slack.
  • Shared files and models. Upload a LoRA once, everyone uses it. Same with checkpoints, input images, reference videos. No duplicate uploads, no version confusion.
  • Team Pages. Organize your workflows and pipelines in one place. Any production studio or VFX company needs a single location to store all workflows their team uses, with headings and workflow details.
  • Team usage dashboard. See who is using what and how much. Pooled FloTime, one invoice, centralized management.

Learn more: Floyo 101 for Enterprise and Teams

Real scenario: Art director hands off to junior artist On Floyo: Art director runs the workflow, likes the result. Junior artist opens the run from team history, sees exact parameters and files, adjusts the prompt, re-runs. Done in 2 minutes.

On RunComfy: Art director exports JSON, sends it over Slack. Junior artist starts their own machine, waits for boot, imports the JSON. "What LoRAs did you use?" "My machine doesn't have that node." The handoff takes 30+ minutes and might not reproduce the same result.

What happens when my workflow needs a custom node?

TLDR Floyo has hundreds of nodes pre-installed and managed. RunComfy gives you ComfyUI-Manager for self-install, but you manage dependencies and installations are per-machine.

Floyo takes a managed approach: hundreds of nodes pre-installed, tested, and maintained. Request a new one and it ships within 24 hours. Enterprise teams can enforce specific nodes per workspace for compliance. The trade-off is you cannot self-install arbitrary nodes.

RunComfy gives you ComfyUI-Manager, the same tool you would use on a local ComfyUI install. You can install whatever you want. The trade-off is dependency management: installations are tied to your machine instance, and switching GPU tiers or losing a Cloud Save may mean reinstalling.

In our testing (June 2026), we ran 10 community workflows from YouTube and Reddit. On Floyo, 9 out of 10 ran without changes. On RunComfy, 7 out of 10 ran after node installs via ComfyUI-Manager. The remaining 3 had dependency conflicts.

The bottom line: if it can be done with ComfyUI, it can be done on Floyo. You are betting on the layer, not one model. Every new model that ships makes Floyo more powerful.

Floyo also has hundreds of models available: open-source, closed-source frontier models (Google, OpenAI, ByteDance), and support for custom-trained models. Both platforms support running ComfyUI online with the full range of popular models like Flux, WAN 2.2, and Qwen Image Edit.

Honest note RunComfy's self-install approach gives power users more flexibility. If you need a bleeding-edge node that was released today, you can install it immediately on RunComfy without waiting for Floyo to add it. The trade-off is stability and reproducibility: managed nodes on Floyo are tested and guaranteed to work together, while self-installed nodes can conflict with each other.

Can I upload my own LoRAs and custom models?

TLDR Both support LoRA uploads. On Floyo, LoRAs are shared across your team. On RunComfy, uploads go to individual storage. RunComfy has a dedicated Trainer with competitive rates ($4.49/hr H100).

On Floyo, you upload once and it is available to your whole team. Everyone can use that LoRA without downloading and re-uploading. This also applies to private models your team has trained in-house.

On RunComfy, LoRA uploads go to your individual storage. There is no team sharing because there are no team features. RunComfy does support fast model downloads from CivitAI and HuggingFace at up to 25x speed.

LoRA training: Both platforms offer on-platform LoRA training. RunComfy has a dedicated Trainer product with competitive rates: $4.49/hr on H100, $5.75/hr on H200, and $29.99/hr on 8xH100 for large-scale training. Floyo trains on H100 NVL GPUs with trained LoRAs automatically shared team-wide.

Honest note If LoRA training is a major part of your workflow, RunComfy's dedicated Trainer product with transparent per-hour pricing and GPU tier selection (including 8xH100 clusters) is a genuine strength. Floyo's training is integrated into the platform and shares results team-wide, which is better for collaborative workflows, but RunComfy gives you more granular control over training hardware.

What is the best platform for sharing ComfyUI workflows?

TLDR Floyo. Creator Page, password protection, analytics, workflow collections. Share a link, recipient clicks Run, same environment. RunComfy has no creator features.

Floyo has a full creator toolkit: your own Creator Page, workflow collections with documentation, password protection for paid content, and usage analytics. RunComfy has none of this.

On Floyo, if it works for you, it works for everyone who clicks Run. Same environment, same nodes, same models. You share a link, they run it. No dependency debugging.

For creators who want to monetize: Floyo lets you password-protect workflows. Gate them behind your Patreon, sell through Gumroad, or include them in a course. You get analytics on views and runs.

Does Floyo or RunComfy have a ComfyUI API? Updated

TLDR Both have a live ComfyUI API with serverless auto-scaling. Floyo: save a workflow, get an endpoint. RunComfy: deploy from Cloud Save with GPU tier selection. Both charge per active GPU second.

Both Floyo and RunComfy now offer ComfyUI API access for deploying workflows as production endpoints. The distinction matters: platforms like Replicate and fal give you an API to a model. Floyo gives you an API to a workflow. A multi-model, multi-node pipeline behind one endpoint. No translation layer, no rewriting your pipeline in code.

On Floyo, Floyo API turns any saved workflow into an HTTP endpoint automatically. Save a workflow, get an endpoint. Send a POST with your inputs, get the output back. Auto-scaling, 100 requests per minute per API key, consumption-based pricing.

On RunComfy, the serverless API deploys workflows from Cloud Save with auto-scaling, configurable min/max instances, queue management, and pay-per-second billing. You select a GPU tier for each deployment, giving hardware flexibility from T4 through H200.

This matters if you are building products that use ComfyUI cloud GPU generation under the hood: an image upscaler, a subtitle generator, an inpainting editor, a batch product photo pipeline.

Key differences:

  • Deployment simplicity: Floyo: save workflow, get endpoint. RunComfy: configure Cloud Save, select GPU, set autoscaling rules, deploy.
  • Hardware options: Floyo: H100 NVL only. RunComfy: 8 GPU tiers from T4 to H200. Choose the right GPU for your workload.
  • Billing: Both charge per active second. Floyo bills from your existing account. RunComfy bills at the GPU tier's hourly rate.
  • Rate limits: Floyo: 100 req/min per API key. RunComfy: configurable queue size and instance count.
Real examples: Apps built on Floyo API Subtitle generator: User uploads a video, picks a language. The app calls a Floyo workflow running Whisper, burns in captions, returns the MP4. Zero ML code. Live demo.

Image upscaler: User uploads a photo, picks 2x/4x/8x. Seed VR 2 runs on Floyo, returns the upscaled image. Live demo.

Inpainting editor: User selects an area, describes what they want. Floyo fills it in using a ComfyUI inpainting workflow. Live demo.
Honest note Both platforms now have competitive API offerings. Floyo's advantage is deployment simplicity and the fact that your interactive and API billing are unified. RunComfy's advantage is GPU tier selection for API deployments: if your API workload runs fine on a T4, you can deploy at $0.79/hr (Pro) instead of paying H100 rates. For cost-sensitive, lower-VRAM API workloads, RunComfy may be cheaper.

Can enterprise teams control which models their team can access? New

TLDR On Floyo, yes. Enterprise admins restrict which models, LoRAs, and nodes their team can access, with an audit trail. RunComfy has no team or access control features.

On Floyo, yes. Enterprise plans include model gating with granular permissions: you decide which models, checkpoints, LoRAs, and nodes your team can use. Everything else is hidden. Admins can enforce different restrictions for different teams. Floyo provides a full audit trail so you see who accessed what and when. See model management docs.

Every model on the platform is tagged in the Floyo Trust Center: Verified Private (the provider will not train on your content) and Commercial Use (outputs are cleared to ship). Floyo's security and compliance posture has been validated by Amazon (MGM Studios MSA) and Netflix (via Native Foreign). For a senior decision maker, the diligence is already done.

On RunComfy, this is not possible. There is no user management, no access control, no way to keep private models restricted to specific team members.

This matters for organizations with compliance, brand safety, or IP concerns. For regulated industries (healthcare, finance, defense) and any business using ComfyUI for commercial use, this kind of access control is a procurement requirement.

Which ComfyUI cloud platform has better GPU hardware?

TLDR Floyo: H100 NVL (94GB VRAM), one tier, no selection needed. RunComfy: 8 tiers from T4 (16GB) to H200 (141GB). RunComfy wins on selection and VRAM ceiling. Floyo wins on simplicity.

Floyo runs NVIDIA H100 NVL GPUs (94GB VRAM, 3.9 TB/s bandwidth). You do not select a GPU. Every workflow runs on the same high-end hardware.

RunComfy offers 8 tiers:

GPUVRAMPay-as-you-goPro rate
T4/A400016GB$0.99/hr$0.79/hr
A10G/A500024GB$1.75/hr$1.39/hr
A600048GB$2.50/hr$1.99/hr
L40S/L4048GB$2.99/hr$2.15/hr
A10080GB$4.99/hr$3.99/hr
H10080GB$7.49/hr$5.99/hr
H200141GB$9.59/hr$7.66/hr

RunComfy's H200 has 141GB VRAM: nearly 50% more than Floyo's H100 NVL. For extremely large models or high-batch workflows, this matters. For most standard workflows (Flux, WAN 2.2, Qwen Image Edit), both platforms have more than enough VRAM.

RunComfy's lower tiers are useful for cost-sensitive work. If your workflow runs on a T4, you can pay $0.99/hr instead of a higher rate. The trade-off is longer generation times on weaker hardware.

Honest note If you need maximum VRAM (141GB on H200) or want to match GPU cost to workload complexity, RunComfy wins on hardware flexibility. Floyo's single-tier approach is simpler: you never worry about selecting the wrong GPU. But you cannot trade down to cheaper hardware for lightweight workloads.

How much does Floyo cost compared to RunComfy?

TLDR Floyo: $12-$56/mo with included generation hours and a free trial. RunComfy: $0.99-$9.59/hr pay-as-you-go, optional $19.99/mo Pro for discounts. Floyo bills generation only. RunComfy bills full sessions.

Floyo pricing (annual billing):

PlanPriceFloTimeTeamStorage
Free Trial$015 min (one-time)110GB (72hr)
Explorer$12/mo3.5 hr/moUp to 520GB
Pathfinder$28/mo10 hr/moUp to 10100GB
Trailblazer$56/mo22 hr/moUp to 10200GB
EnterpriseCustomUsage-basedUnlimitedCustom

All paid plans include Flex FloTime top-ups at $7/hour. Annual billing saves 20%. Partner Nodes credits included for closed-source model APIs ($0.75 on free, $5-$15 on paid plans).

RunComfy pricing:

  • Pay-as-you-go: $0.99-$9.59/hr depending on GPU tier. No subscription required.
  • Pro subscription: $19.99/mo. Includes 20%+ discount on all GPU rates, $10 monthly credit, 200GB permanent storage, 20 CPU hours/month, priority support.
  • Trainer: $4.49/hr (H100), $5.75/hr (H200), $29.99/hr (8xH100). Pro discount applies.
  • Free tier: Free account creation, but no GPU time included. Must add funds to run workflows.
Cost comparison: 10 hours of actual generation per month On Floyo (Pathfinder): $28/mo flat. Includes 10 hours of generation time. Non-generation time is free. Team features included.

On RunComfy (A6000, no Pro): If 10 hours of generation means roughly 30 hours of total machine time (building, reviewing, iterating): 30 x $2.50 = $75/mo. With Pro ($19.99/mo + $1.99/hr x 30h): $79.69/mo.

On RunComfy (T4, no Pro): If you can use a T4: 30 x $0.99 = $29.70/mo. Comparable to Floyo's Pathfinder, but on weaker hardware with no team features.
Honest note The pricing comparison depends heavily on how you use ComfyUI. If you are a power user who generates almost continuously with minimal idle time, RunComfy's hourly billing on a lower-tier GPU can be competitive. If you spend a lot of time building workflows, reviewing outputs, and iterating (most users do), Floyo's generation-only billing saves money. The only way to know for sure: run the same workflow on both platforms and compare your actual costs.

What does RunComfy do well?

This is a Floyo page, so we want to be upfront about where RunComfy is a strong ComfyUI cloud alternative:

  • Widest GPU selection. 8 tiers from T4 to H200. Match your hardware to your workload and budget. No other ComfyUI cloud platform offers this range.
  • True pay-as-you-go. No monthly commitment. Add funds, use them. Good for sporadic or experimental usage where a subscription does not make sense.
  • Full ComfyUI environment. ComfyUI-Manager lets you install any node. Configure everything like a local machine. Power users who want total control will prefer this.
  • Dedicated LoRA Trainer. Transparent per-hour pricing, GPU tier selection for training (including 8xH100 clusters), and competitive rates. If training is a major part of your workflow, RunComfy's Trainer product is strong.
  • Strong content ecosystem. RunComfy has extensive guides, tutorials, troubleshooting content, and node documentation. Their learning resources are excellent for ComfyUI newcomers.
  • Use-case landing pages. RunComfy creates dedicated pages for specific creative use cases (logo generators, poster makers, thumbnail tools) that show what ComfyUI can do for specific needs.
  • Competitive API offering. Their serverless API is live with auto-scaling, deployment versioning, rollback, and GPU tier selection per deployment.
  • H200 GPU availability. 141GB VRAM on the H200 is the highest available on any ComfyUI cloud platform. For extremely large models, this is the only option.

For solo power users who want full control, no monthly commitment, and the ability to choose their GPU tier, RunComfy is a reasonable choice.

Should I use Floyo or RunComfy?

Use Floyo if:

  • You work with a team, even one other person
  • You want predictable monthly costs without idle billing
  • You want instant starts with zero machine management
  • You need shared LoRAs, checkpoints, and run history across your team
  • You want to build apps or tools on top of your workflows (API)
  • Your enterprise needs to control which models your team can access
  • You are a creator who shares or sells workflows
  • You are new to ComfyUI and want hundreds of ready-to-run workflows without managing nodes
  • You want a free trial to evaluate before spending anything

Use RunComfy if:

  • You want a full, controllable ComfyUI environment with ComfyUI-Manager
  • You prefer pay-as-you-go without a monthly subscription
  • You want to select your GPU tier (T4 through H200)
  • You need H200-level VRAM (141GB) for extremely large models
  • LoRA training at dedicated Trainer rates is a major part of your workflow
  • You work solo and do not need collaboration features

Which ComfyUI cloud platform should I use for my use case?

Small animation studio (3-5 people) Recommendation: Floyo. Shared run history means the team iterates without re-sharing files. Pooled billing, team pages for organizing pipelines, and no idle billing during review sessions. RunComfy has no team features, so each artist would manage their own machine independently.
Solo ComfyUI power user Recommendation: Either works. Floyo for simplicity and predictable billing. RunComfy for full environment control and GPU tier selection. If you want to install bleeding-edge nodes yourself, RunComfy. If you want managed nodes and instant starts, Floyo.
Heavy LoRA training Recommendation: RunComfy for training, Floyo for production. RunComfy's dedicated Trainer product has competitive rates ($4.49/hr H100) and 8xH100 clusters. Train on RunComfy, upload the trained LoRA to Floyo for team production workflows.
Workflow template sales / creator monetization Recommendation: Floyo. Creator Page, password protection, analytics, collections. RunComfy has no creator or monetization features.
Production API integration Recommendation: Both competitive. Floyo for deployment simplicity and unified billing. RunComfy for GPU tier selection per deployment and deployment versioning. If your API workload can run on cheaper GPUs (T4/A10G), RunComfy may be more cost-effective.
Enterprise / regulated industry Recommendation: Floyo. Model gating, access control, audit trail, commercial-use warranty, Trust Center. RunComfy has no enterprise features.

Floyo vs RunComfy: Frequently asked questions

Does RunComfy charge for idle time?
Yes. On RunComfy, you pay for the full machine session including time spent building workflows, writing prompts, downloading models, and reviewing outputs. On Floyo, you pay only for active generation seconds.

Can I self-install custom nodes on Floyo?
No. Floyo has hundreds of nodes pre-installed and managed. You can request new nodes and they are added within 24 hours. On RunComfy, you can self-install any node via ComfyUI-Manager.

Does RunComfy have team collaboration?
No. Each user operates an individual machine. Cloud Save preserves your personal environment, but there is no way to invite teammates or share assets within a workspace.

Which platform is better for heavy video models (WAN 2.2, HunyuanVideo)?
Both support them. Floyo runs on H100 NVL (94GB VRAM). RunComfy offers up to H200 (141GB VRAM). For most video workflows, 94GB is sufficient. If you need maximum VRAM for extremely large models or high batch sizes, RunComfy's H200 has the edge.

Does Floyo have an API for ComfyUI workflows?
Yes. Floyo API turns any saved workflow into an HTTP endpoint. Standard POST requests, auto-scaling, 100 req/min, consumption-based pricing. Live production apps already running on it.

Does RunComfy have an API?
Yes. RunComfy's serverless API deploys workflows from Cloud Save with auto-scaling, GPU tier selection, deployment versioning, and pay-per-second billing.

Can I restrict which AI models my team can use?
On Floyo enterprise plans, yes. Admins gate which checkpoints, LoRAs, and nodes team members can access. Includes user management, permissions, and an audit trail. RunComfy has no access control features.

How much does Floyo cost vs RunComfy?
Floyo starts at $12/month (3.5 hours of generation time) with a free trial. RunComfy is pay-as-you-go starting at $0.99/hour on a T4. Different billing models: Floyo charges for generation only, RunComfy charges for full session time including idle.

Which platform has more custom node support?
Floyo has hundreds pre-installed and managed, with new nodes added within 24 hours. RunComfy lets you self-install any node via ComfyUI-Manager. Floyo has broader out-of-the-box coverage. RunComfy has more flexibility for power users who want to install their own.

Which ComfyUI cloud platform should I choose for my animation studio?
Floyo. Animation studios need team collaboration, shared assets, and predictable billing during long review sessions. RunComfy has no team features and charges for idle time during creative reviews.

Is Floyo or RunComfy better for beginners?
Floyo. It has hundreds of ready-to-run workflows organized by creative outcome. Click a workflow, click Run, see results. No GPU selection, no machine management, no node installation. The free trial lets you learn without spending anything. RunComfy requires GPU selection and machine management, which can be intimidating for newcomers.

Can I use ComfyUI for commercial use on these platforms?
ComfyUI itself is free for commercial use under the GPL license. On Floyo, commercial use is explicitly supported: every model tagged for commercial-use and data-privacy status, US data residency, compliance validated by Amazon (MGM Studios MSA) and Netflix, and a public Trust Center that verifies every model. On RunComfy, check their terms. Enterprise teams should verify licensing and IP protection before deploying either platform.

Is this page biased? (RunComfy vs Floyo)
Yes, this is a Floyo page. We are transparent about that. We have included a "What does RunComfy do well?" section and honest notes throughout that acknowledge where RunComfy wins. We tested both platforms in June 2026 and verified pricing from official sources. If you find any inaccuracy, contact us.

Our recommendation: Floyo vs RunComfy

If you are looking for the best ComfyUI cloud platform for teams and production work, use Floyo. If you are a solo power user who wants full environment control and GPU tier selection, RunComfy is a strong ComfyUI cloud alternative.

If you want to run ComfyUI online without managing infrastructure, both platforms work. Floyo is simpler (serverless, instant starts, no GPU selection). RunComfy gives you more control (full environment, 8 GPU tiers, ComfyUI-Manager).

If ComfyUI feels complex, think of it this way: the workflow is the car. Most people just drive it. Open a workflow, read the instructions, change the inputs, and run. The node graph is under the hood. Only when you need it to become something else does someone go under the hood. A small number of team members handle that, and their expertise compounds across the whole team.

Start with Floyo's free generation time. Test your workflows, invite a teammate, see if the collaboration features match how you work. 15 minutes of GPU time is enough to make an informed decision.

If you are evaluating RunComfy, add funds and test a workflow on the GPU tier you would actually use. Compare the total session cost (including idle time) against Floyo's generation-only billing. The math varies by workflow and work style.

Try Floyo free. 15 minutes of GPU time. No credit card.

Test your workflows, explore team features, run your first generation.

Start free trial View pricing

Last updated: June 2026. Written by the Floyo team. We tested both ComfyUI cloud platforms in June 2026 using WAN 2.2 video workflows, Flux image workflows, and custom node-heavy pipelines. Pricing verified from official sources on June 24, 2026.
Floyo Pricing · RunComfy Pricing

Table of Contents
OVERVIEW

Floyo vs RunComfy compared: serverless vs machine-instance ComfyUI cloud platforms. Team collaboration, ComfyUI API, custom nodes, GPU tiers, pricing. Both tested June 2026 with honest trade-offs.