Gumloop vs n8n: AI-first against general-purpose
One is built around language models and priced in credits with an orchestration fee, the other is a general workflow engine priced per execution. Which suits AI-heavy work, and which suits everything else.
Osman Ramadan10 min read
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These two are aimed at different problems, which makes the comparison more useful than most. Gumloop is built around language-model workflows and prices accordingly. n8n is a general-purpose automation engine with AI available as one capability among many, priced by workflow execution.
If most of your work involves a model reading, classifying, or generating something, the two are genuinely comparable. If your automations mostly move data between systems with occasional AI, n8n is the more sensible starting point and the comparison largely resolves itself.
Prices were checked against each vendor's pricing page in September 2026 and change often.
What we'll cover
What each is built around
Gumloop treats the language model as the centre of the workflow rather than a step within it. Its building blocks assume you are extracting, classifying, summarizing, or generating, and it provides access to a wide range of models — more than 35 at the time of writing — with the option to bring your own API keys. Recent product direction has moved further toward agents and company-wide context, with features like a shared knowledge base the workflows can draw on.
n8n is a workflow engine first. Nodes connect systems, transform data, branch on conditions, and loop over collections, with AI agent and model nodes available among several hundred others. Code nodes let you drop into JavaScript or Python where the built-in nodes fall short. It is self-hostable, which Gumloop is not.
The practical consequence: Gumloop makes AI-heavy work pleasant and constrains what else you can do; n8n makes everything possible and asks more of you for the AI parts.
The pricing, including a fee people miss
Gumloop Pro starts at $37 a month, including 20,000 credits, unlimited seats, and unlimited teams. Enterprise is custom-priced. There is a 14-day trial rather than a permanent free tier.
The detail worth reading carefully is the 8% orchestration fee. On top of the subscription and the credits, Gumloop applies a percentage fee on orchestration. If you bring your own model API keys, that fee still applies to the orchestration layer. It is disclosed plainly on the pricing page and it is easy to skim past when comparing headline numbers, and at volume it is a real line item rather than a rounding error.
n8n bills by workflow execution regardless of complexity. Starter is £20 a month billed annually for 2,500 executions; Pro is £50 a month billed annually for 10,000. Every plan includes unlimited users, unlimited workflows, and every integration. Annual billing saves 17%. Self-hosting the community edition costs nothing in licence.
The models reward opposite things. n8n does not care how many steps a workflow has, so complexity is free and frequency is what costs. Gumloop's credits are consumed by what the workflow actually does, so model-heavy runs cost more than trivial ones, which is arguably the fairer arrangement for AI work and harder to forecast.
The same workload, priced both ways
A research workflow: 200 runs a month, each making a dozen model calls over long documents. Gumloop: this is what it is for, and the credit consumption is meaningful given the document lengths, with the 8% orchestration fee on top. n8n: 200 executions is trivially inside Starter at £20, and you pay your model provider directly for the twelve calls. n8n plus your own API keys is very likely cheaper here; Gumloop is likely faster to build and easier to iterate on.
A data-sync workflow: 20 steps, 5,000 runs a month, no AI at all. n8n: 5,000 executions on Pro at £50, and the twenty steps cost nothing extra. Gumloop: this is not the tool, and paying an AI-workflow platform plus an orchestration fee for work involving no AI makes little sense. n8n wins outright.
A classification workflow: 10,000 short messages a month, one model call each. Gumloop: 10,000 light credit consumptions, comfortably within the Pro allowance, and the build is quick. n8n: 10,000 executions puts you on Pro at £50 plus model costs. Genuinely close, and the deciding factor is usually who is building rather than the money.
The pattern: n8n's execution pricing rewards complex, low-frequency work; Gumloop's credit pricing rewards work where the AI is doing something proportionate to what you are charged.
Building and who can do it
Gumloop's builder is more approachable for non-developers working on AI tasks. The components map onto things people actually want — read this, classify that, write this up — rather than onto generic data operations. Someone in marketing or research can assemble something useful without understanding data structures.
n8n rewards technical users and can frustrate everyone else. Data moves between nodes as structured items, and understanding that structure is the difference between finding n8n powerful and finding it obstructive. For a developer it is excellent; for an operations colleague it is a real learning curve.
Neither removes the underlying translation work: holding the process in your head and expressing it in the tool's vocabulary. That is what conversational building removes rather than eases. On CodeWords you describe the process in plain language and Cody, the automation builder, builds it, connects it to the tools you already use, and deploys it, with more than 3,000 integrations available. The free plan covers light use, with Pro at $39 per month and Business at $100 per month as usage grows; details are on the pricing page.
Integrations and reach
n8n's catalog runs to several hundred nodes, and its generic HTTP Request node reaches anything with an API. That combination means a missing integration is usually a documented API call rather than a blocker, which makes the headline catalog number less important than it looks.
Gumloop's catalog is narrower and focused on the tools that matter for AI workflows: document sources, web scraping, search, spreadsheets, and communication tools. That focus is deliberate and it is a genuine limitation if your process touches an unusual line-of-business system.
The useful check for either is the same: name the three to five systems your process actually touches and confirm both cover those, rather than comparing catalog sizes neither of you will exhaust.
What to test before committing
A two-day trial on each answers more than any comparison, including this one. Four things worth doing deliberately.
Build your second-hardest process, not your simplest. The easy one works everywhere and tells you nothing. Something with a condition and two systems shows you where each tool strains.
Feed it your actual data, including the awkward records. The document with the unusual layout, the message in another language, the record with a missing field. Model-based workflows behave very differently on clean test data than on real inputs, and this is the fastest way to find out.
Price it at ten times your current volume. Count your runs and your steps, apply Gumloop's credits plus the 8% orchestration fee, and n8n's execution count plus your model provider's charges. Automation spreads once it works, and a bill that is comfortable in month one can be uncomfortable by month six.
Hand it to a colleague and ask for a change. If they cannot work out how, you have found your maintenance cost. This matters more on n8n, where understanding the data structure between nodes is the barrier.
Which to choose
Gumloop if language models are the point of the work rather than a step in it, if the people building are not developers, if you want many models available without managing access to each, or if you value building quickly over controlling every detail.
n8n if your automations are mostly system-to-system with occasional AI, if you need self-hosting for data residency or cost, if your team is technical, or if your workflows are complex enough that per-execution pricing saves real money.
Either, with care about the fee. If you are comparing on cost, model Gumloop with the 8% orchestration fee included and n8n with your model provider's charges included. Comparing a subscription against a subscription will mislead you in both directions.
Frequently asked questions
Can Gumloop be self-hosted?
No. It is a managed cloud product. If self-hosting is a requirement, whether for data residency, cost at volume, or policy, n8n is the option of the two that supports it.
What exactly is the 8% orchestration fee?
A percentage fee applied to orchestration on top of the plan, disclosed on Gumloop's pricing page. It applies alongside the credits, including when you bring your own model API keys. Include it when modelling cost, because comparisons that ignore it understate Gumloop against per-execution competitors.
Does n8n have AI features?
Yes, including AI agent nodes, model nodes, and tool-calling, and the cloud plans include AI credits. They sit inside a general-purpose tool rather than defining it, so they are capable without being the product's centre of gravity.
Which is better for processing documents?
Gumloop, for most teams, because document reading and extraction is the shape of work it was built for and its components assume it. n8n can do the same with model nodes and more assembly, which is worth it if the surrounding workflow is complex.
Is bringing my own API keys cheaper?
Usually, since you pay the model provider's rate directly rather than a platform's markup. On Gumloop the orchestration fee still applies, so the saving is on the model calls rather than on everything. On n8n, using your own keys through HTTP or model nodes means you pay the provider directly with no platform margin on the tokens.
Which has the better free option?
n8n, if you count the self-hosted community edition, which is free indefinitely and costs you a server and your time. Gumloop offers a 14-day trial rather than a permanent free tier, so evaluating it has a deadline.
How do the two handle long-running workflows?
n8n's concurrency limits — five on Starter, twenty on Pro — are the constraint to check, since a long-running workflow occupies a slot. Gumloop's credit model means duration matters less than what the run actually consumes. For anything that waits on a human or an external system for hours, check the specific timeout behaviour on whichever you pick.
Which is better if my team is a mix of technical and non-technical people?
This is the case where the two fight hardest. n8n gives your developers everything they want and leaves your operations colleagues dependent on them. Gumloop lets the operations side build and limits what the developers can do when a workflow outgrows it. Mixed teams frequently end up running both, which works and means two tools to administer and a question about where each new automation belongs.
Does n8n's execution limit count failed runs?
A run that starts consumes an execution whether or not it succeeds, which matters if something is failing repeatedly. Worth setting up alerting on failures rather than discovering the pattern in a usage graph at the end of the month.
Can I start on one and move to the other later?
You can, and it is a rebuild rather than a migration, since neither exports into the other's format. The practical hedge is to write down what each workflow does as logic — trigger, steps, output, exceptions — separately from whichever tool currently runs it. That description survives any move and takes minutes to keep current.
Which is faster to get a first working automation?
Gumloop, for AI work, by a clear margin: the components map onto the task rather than onto generic data operations, so there is less to learn before something useful runs. n8n is faster for anyone who already thinks in terms of APIs and data structures, and slower for everyone else.