Gumloop vs n8n: Agents for Ops Teams or Workflows for Engineers

Gumloop and n8n differ most on one question: who decides what happens next. In Gumloop, you give an AI agent a goal and a set of tools, and the agent picks the steps. In n8n, you draw the workflow, and every step runs the way you wired it. Billing, hosting and who on your team can maintain the thing all follow from that choice.

Gumloop's own docs now describe it as an AI agent platform, and its pricing page lists the older workflow builder as a legacy item. Some older write-ups still describe Gumloop as a drag-and-drop flow tool, so check what you are actually comparing before you read further.

• Gumloop: cloud product, agents plan their own steps, billed in variable credits, aimed at teams who want to describe work rather than diagram it
• n8n: workflow canvas with an AI Agent node inside it, billed per whole workflow run, self-hostable under a source-available licence
• The dividing question: do you want the model to decide the path, or do you want to decide the path and let the model handle one step?

Quick comparison

Who builds and who owns it

Gumloop is built for someone who can describe the job. Its agent docs describe three moves: add the connectors the agent needs, give it a real task, then ask it to write its own instructions from what worked. There is no canvas to lay out. The agent decides which tools to call and in what order, and adapts when a result surprises it.

That is fast for an ops lead, and it has a cost. The path is not fixed, so two runs of the same task can take different routes. Reviewing a run means reading what the agent did, not checking a diagram.

n8n is built for someone who wants the path fixed. Its AI Agent node lets you connect a chat model and tools so an agent can choose among them, but that agent sits inside a workflow you designed. The trigger, the branching, the error handling and the destination are all yours. Code steps in JavaScript and Python are part of normal use, and the people who maintain n8n well tend to be comfortable with JSON and expressions.

The practical split:

• A non-engineer owns the automation and the work is judgement-shaped (triage, research, drafting): Gumloop's model fits
• An engineer owns it and the work has to behave the same way every run (sync, routing, ETL with a model in one step): n8n's model fits

Billing: credits per task vs executions per run

These two meters are not comparable by line item, and that is the main trap in cost comparisons.

Gumloop bills credits that vary with what the agent does. The credits doc says outright that the same agent can cost very little for a quick question and far more for a deep research task. A task's cost is built mainly from four parts: the model's reasoning, each connector call, the time the agent spends actively working, and an orchestration fee on top. Longer conversations and more connected tools make the model part larger. You cannot predict cost from step count, because the agent decides the step count.

n8n bills per execution, and an execution is one run of the whole workflow. The pricing page states that cost is based on monthly workflow executions regardless of complexity, with unlimited steps. n8n's executions doc adds the detail that matters for budgeting: only production executions count toward the quota, and a webhook trigger counts one execution per inbound request.

What that means in practice:

Neither meter is better. Per-execution billing rewards workflows that do a lot per run. Variable credits reward tasks that are worth the agent's effort. For how credits compare with Zapier's per-step tasks, see Gumloop vs Zapier; for where credit-based pricing starts to hurt, see Gumloop alternatives.

Licence and self-hosting

This is the clearest hard difference, and the one most people get slightly wrong.

n8n can run on your own infrastructure. The hosting docs say that without a licence key, a self-hosted install runs as the free Community edition, and a Business or Enterprise key unlocks those editions. The pricing page also points to the Community Edition on GitHub.

It is not open source in the OSI sense. The code is under the Sustainable Use License. That text lets you use or modify the software for your own internal business purposes or for non-commercial or personal use, and it only permits distributing it to others free of charge for non-commercial purposes. The same file says that source files with .ee. in the name, or in an .ee directory, are not under that licence and require an n8n Enterprise licence. If you build a product on top of n8n and resell it, get legal advice first.

Gumloop's pricing page and docs show no downloadable self-hosted edition. What they do show is an Enterprise arrangement: the credits doc notes that Enterprise customers running Gumloop in their own VPC are not charged for compute, because it runs on their infrastructure, and the pricing page lists a Virtual Private Cloud as an optional Enterprise item. That is a contract conversation, not a Docker image.

If your constraint is that data cannot leave your network and you want to start today, n8n self-hosted is the direct answer. If your constraint is the same but you have a budget and a procurement process, both are on the table.

AI agent capabilities

Both now support agents, so the useful comparison is where the agent lives.

In Gumloop, the agent is the product. The docs describe a sandbox where agents run Python and shell commands, a real Chromium agent browser for sites with no connector, saved skills, scheduled, app and webhook triggers, and human approval settings you can apply per connector so that reads run freely and writes ask first. The browser is the notable one: it can open sites, sign in with saved logins and fill forms, and hand control back to you at a login or CAPTCHA.

In n8n, the agent is a node. Its docs describe requiring human approval before the agent runs specific tools, sending the request through a channel such as Slack or the n8n Chat interface. The platform also has a built-in MCP server, so an AI client such as Claude or ChatGPT can build and run workflows in your instance. The agent gets the surrounding workflow's reliability: retries, error branches, and Git version control on the editions that include it.

Neither is strictly more capable. Gumloop gives the agent more freedom and more built-in abilities. n8n gives you more control over the surrounding system.

A concrete split

• Triage and research tasks (read a batch of inbound emails, enrich leads, summarise a competitor's pricing changes): Gumloop, where the agent's judgement is the work.
• Pipelines that must be auditable (move records between systems, apply fixed rules, call a model for one classification): n8n, where the path is the point.
• Regulated or private data: n8n self-hosted unless your organisation will negotiate a private-cloud contract.
• A mixed estate: use n8n for the plumbing and let it call a reasoning agent only where a rule cannot decide.

When neither fits

Both tools assume you are designing the automation, whether as an agent brief or a canvas. A lot of useful AI work is the opposite: somebody has already built a setup that works, and your problem is running it.

Taku is an AI-native desktop workspace for that case. It mirrors a working AI setup into a desktop workspace and runs it, so you can use a configuration someone else got right without rebuilding their environment first. It does not replace Gumloop or n8n. Taku is in Beta, and the Mac app is available now. The free app library shows what that looks like. If your real question is about the wider field, our n8n alternatives guide covers it.

Deciding

1. Must the data stay on your own servers, starting now? Yes: n8n self-hosted.
2. Who will maintain it? A non-engineer: Gumloop. An engineer: n8n.
3. Must every run take the same path? Yes: n8n. No, and judgement matters: Gumloop.
4. Is your cost driven by long workflows or by long model tasks? Long workflows: per-execution billing. Long model tasks: expect model usage to dominate on either.
5. Does the work involve sites with no API? Gumloop's agent browser is built for that.

FAQ

Is Gumloop better than n8n?

Neither wins outright. Gumloop suits people who want to describe a task and let an agent work out the steps. n8n suits people who want to design and own the workflow, including where it runs.

Is n8n free?

The self-hosted Community edition runs without a licence key, and you cover the server and its upkeep. n8n Cloud and the Business and Enterprise editions are paid; see the pricing page for current terms.

Can I self-host Gumloop?

Its pricing page and docs list no downloadable edition. They do mention Enterprise customers running Gumloop in their own VPC, which is arranged with the vendor.

Is n8n open source?

No. n8n's own licence page calls it fair-code and says it does not call itself open source, because the Sustainable Use License limits use to internal business, non-commercial or personal purposes. Files marked as Enterprise are under a separate licence.

How does Gumloop pricing work compared with n8n?

Gumloop bills credits that vary with the model used, connector calls, working time and an orchestration fee. n8n bills one execution per workflow run, regardless of how many steps it contains.

Can n8n build AI agents like Gumloop?

Yes, through its AI Agent node, which chooses among tools you connect. The difference is that the agent runs inside a workflow you designed, rather than being the whole product.