I'm still looking for a cab service that shows the full price range before I even book. Something like: "Base fare $12 + possible surge $0-$4 depending on traffic and demand." Hey, I can dream.
Gumloop's pricing gets close to that idea. It's transparent, but since it runs on credits, the total cost can still vary based on how your workflows run and how often you run them. Knowing the possible range makes it easier to plan without mentally refreshing the meter.
In this guide, I'll break down how much Gumloop's credit-based pricing really costs and give you a clear overview of its pricing. I'll also compare Gumloop's and Zapier's pricing so you can get a better sense of what you'll actually pay as you scale.
Table of contents:
Gumloop pricing overview
Here's a quick snapshot of Gumloop's pricing.
Plan | Price | Credits | Seats | Key features | Best for |
|---|---|---|---|---|---|
Pro | $37/month | 20,000/month | Unlimited | 5 concurrent runs, 25 concurrent agent chats, and team analytics | Growing teams using AI regularly |
Enterprise | Custom | Custom | Unlimited | Advanced security, audit logs, VPC, and access controls | Large teams with compliance needs |
Gumloop has been refining its tiers, but in doing so, it's removed its free tier and its lower-level entry tiers.
How much Gumloop's credit-based pricing really costs
Gumloop runs on a credit system. Gumloop credits are like arcade tokens for AI workflows—every action costs a few tokens, but the exact number depends on how complex the move is. A simple step might barely dent your credit balance, while a heavy AI task can chew through credits faster than a group chat burns through memes.
The base plans
Gumloop doesn't offer a free plan. You start with a 14-day trial of Pro, which includes enough credits to test ideas and build small AI-powered workflows. Once the trial ends, you're on paid Pro unless you've canceled.
The Pro plan starts at $37 per month and includes 20,000 credits each month, unlimited seats, up to 5 concurrent legacy workflow runs, and up to 25 concurrent agent chats. Unused credits don't roll over. Each credit is worth $0.005, so you can use that to compare Gumloop against other tools. The Enterprise plan has custom pricing and credits, and adds governance features such as role-based access controls, audit logs, SCIM/SAML, and optional private infrastructure for teams with stricter security requirements.
Because credits reset every month, your plan only covers what you actually use that month. If your workflows or agents run more than expected, you'll need to buy more credits or turn on overage billing (more on that below).
Basic vs. advanced task fees
Not all actions cost the same number of Gumloop credits. Gumloop now bills most work as agent chats, and each chat adds up four things:
AI model usage: Billed at the model provider's list price, divided by $0.005 per credit. For example, a $0.03 model call costs 6 credits. Bigger models and longer prompts cost more.
Tool calls: Every successful connector call costs at least 1 credit, including apps like Slack, Google Sheets, and Gmail. Failed calls aren't charged. Some tools, like data enrichment or web scraping, add their own charge on top of that credit.
Compute: 5 credits per minute of session time.
Orchestration fee: An 8% fee on top. If you bring your own model API key, token credits drop to zero, but the fee rises to 16%.
The upside: you get fine-grained control over powerful AI workflows. But costs aren't flat—think in terms of what each step does, not just how often it runs.
Watch out for credit overages
Credit systems reward efficiency, but they can surprise you if an agent or workflow runs more often than expected. Since every successful connector call costs at least 1 credit, a loop or a large enrichment job can burn through a monthly allocation quickly.
What happens when you run out: agents stop. Pay-as-you-go overage is off by default. If you turn it on, extra credits cost $0.005 each. On Pro, overage is capped, with a default ceiling of 1,000,000 overage credits ($5,000) per billing period, and you can set a lower cap in your billing settings.
Who is Gumloop best for?
Gumloop is built for people who want serious control over how AI behaves inside their automations. Among modern workflow automation tools, it leans heavily toward customization, experimentation, and prompt-driven logic.Â
Here's who can benefit the most from Gumloop:
Technical builders creating multi-step AI prompt chains that reason, summarize, classify, and transform data across several steps
Ops and research teams running large-scale web scraping and enrichment workflows across many sources
Growth teams experimenting with AI-first processes where the workflow itself evolves over time
Companies building internal AI tools that require structured logic layered on top of LLM outputs
Teams comfortable monitoring usage closely as workflows scale and consume credits
If your processes involve deep prompt tuning or complex data extraction, Gumloop can feel incredibly powerful. But you're also relying on AI for everything. This can cost a lot, using hefty AI credits when all you really needed was a deterministic workflow. Â
Gumloop vs. Zapier pricing
The real difference between Zapier and Gumloop often comes down to bloat. Gumloop prices by usage: model tokens, a credit for each connector call, compute time, and an orchestration fee. Agent chats make costs vary even more, since those depend on conversation length, the AI model used, and how many actions the agent takes.
Zapier's task costs are more uniform, and you only add AI when you need it—it's not AI for AI's sake. You also only pay for completed actions, so you won't be paying for internal logic or triggers
| Gumloop | Zapier |
|---|---|---|
Pricing model | Credit-based (14-day Pro trial, no free plan) | Task-based (free tier available) |
How costs are calculated | Varies by model usage, tool calls (1+ credit each), compute time, and an 8% orchestration fee | Fixed cost per completed task (1 task for standard actions, 3 or 5 tasks for advanced or premium AI models) |
Cost predictability | Less predictable—depends on how workflows run | More predictable—easier to estimate monthly usage |
Complex AI workflows | Can get expensive quickly (more credits per run) | Still predictable (tasks per action) |
Scaling across teams | Requires active credit monitoring | Easier to budget as usage grows |
Best for | AI-only workflows | Consistent, scalable automation with AI built in |
Zapier tends to feel steadier month to month—and task use stays under control with deterministic workflows available—while Gumloop rewards teams willing to actively manage credit usage as workflows evolve.
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This article was originally published in June 2026. The most recent update was in November 2026.
