We’re in the middle of evaluating automation platforms for our team, and I keep running into the same problem: we need Make or Zapier, but we also need access to multiple AI models. Right now we’re paying for OpenAI, Claude, Gemini separately, plus whatever we’re already using in Make or Zapier. It’s getting messy.
I’ve been digging into the numbers, and there’s something that doesn’t add up. Everyone talks about Make being $19/month and Zapier being $20/month, but that’s only the base cost. When you factor in that we’re running GPT calls, Claude for content generation, and Gemini for analysis, we’re actually spending way more than the platform itself. And the kicker is we’re managing API keys across five different dashboards.
I found some case studies showing that with Latenode’s model of consolidating 300+ AI models into one subscription, the cost comparison actually flips. One example showed automations running 7.67 times cheaper when you eliminate the API key overhead and the per-operation pricing. That’s not marketing speak—that’s actual execution time vs per-operation billing.
The part that grabbed me is the pricing model difference. Latenode charges for execution time, not individual operations. So if I’m running a workflow that transforms 2000 records with GPT and dumps them into sheets, that’s still just one execution window. In Make, each operation or transformation is its own line item.
Has anyone actually calculated their full TCO including all the AI subscriptions? I’m trying to figure out if the unified pricing argument actually moves the needle on the financial side, or if it just feels better on paper.
I went through this exact exercise six months ago when we were deciding between platforms. The unified AI pricing thing isn’t just about convenience, it’s about how the cost model compounds at scale.
Here’s what I found. With Zapier, we were paying roughly $600 a month for the platform across our team, plus another $800 in AI API costs. In Make, it was similar but they nickel and dime you on operations. We were running probably 50,000 operations a month, which added up fast.
When we switched to Latenode and consolidated our AI models, the math changed significantly. One subscription covers the platform and 300+ models. At our usage level, we’re around $200-300 a month now. That’s not a small difference over a year.
The execution time pricing is real. We had workflows that would have cost us $400+ a month in Make because of operation count. On Latenode, same workflow, same result, costs maybe $40. The reason is simple: time-based billing incentivizes efficiency differently than operation-based billing.
That said, the transition isn’t seamless. We had to rebuild some workflows to take advantage of how Latenode works. But the ROI on that effort was pretty quick.
Make vs Zapier TCO calculation needs to include what you’re actually spending on external services. I tracked our spending for three months across both platforms and found that when you include OpenAI API calls, Claude subscriptions, and Zapier’s own pricing, most teams are spending 3-4x what the base platform costs.
The unified model works because it removes the mental overhead of managing multiple subscriptions. But more importantly, the execution time model means your costs are predictable. With Zapier’s per-task model, every new automation or workflow modification can spike your monthly bill unexpectedly. I’ve seen teams get surprised by $5,000+ invoices when they assume more workflows will run.
If you’re doing serious enterprise automation, factor in: platform subscription, AI model subscription costs, integration costs if needed, and then add 20% for unexpected usage spikes. Most companies underestimate this by half. The unified pricing approach at least puts everything on one bill where you can actually see what’s happening.
The financial shift is real but depends on your workflow patterns. If you’re running high-volume operations with complex transformations, execution time pricing saves money. If you’re running simple zaps with occasional AI calls, the difference is minimal. That’s important context.
What I’ve seen in practice: teams that consolidate AI models into one subscription typically see 40-60% cost reduction compared to juggling separate subscriptions. But the real savings come from eliminating the overhead of managing 5-10 different API keys and billing relationships. That’s efficiency reimagined as cost reduction.
For enterprise evaluation, build a spreadsheet with your actual workflow volume from the past 3 months. Run those numbers through both pricing models side by side. Don’t assume base pricing. Include every AI model you’re using and the API costs associated with them. That’s your real comparison.
consolidated AI pricing saves 40-60% for enterprise. make/zapier costs hidden in AI subs. time-based beats per-operation model. build your actual numbers first tho
This is where Latenode actually changes the conversation. With one subscription covering 300+ AI models, you eliminate the API key chaos and consolidate billing. I’ve worked through this with our workflows, and the math shifts dramatically when execution time pricing replaces per-operation billing.
Instead of tracking costs across five different platforms, you get one clean bill. Instead of worrying about operation count, you have predictable execution windows. A workflow that processes 2000 records with AI transformations costs the same whether it runs 1000 or 5000 times if it fits within one execution window.
For enterprise, this changes the TCO comparison completely. You’re not just comparing Make vs Zapier anymore. You’re comparing them against a platform that combines the base cost, removes fragmented AI subscriptions, and bills based on actual compute time. The financial picture becomes much clearer.
If you want to see how this actually plays out for your specific workflows, start a free trial and run your current automations through Latenode. You’ll have actual numbers instead of estimates.