The messaging around “one subscription for 400+ AI models” sounds clean on the surface. No more separate vendor bills, no more choosing between subscriptions. But I’m wondering how much complexity is hidden behind that claim when you’re actually trying to calculate total cost of ownership for an enterprise.
Like, are all 400 models equally available? Do you pay the same price for GPT-5 as you do for a smaller, specialized model? Are there hidden tiers where premium models cost more? And more importantly, how do you actually model this against Make or Zapier pricing when they use completely different billing structures?
We’re trying to do an apples-to-apples comparison. Make charges per operation, Zapier charges per task, and then some platforms want to add AI model pricing on top or include it in the base. The comparison matrix keeps breaking down because we’re not actually comparing the same thing.
I’m also wondering: does having access to 400 models actually solve any business problems, or is that just a feature count? We use maybe 5-6 models regularly. Are we paying for 395 models we’ll never touch?
Has anyone actually worked through the TCO math on this and figured out whether consolidation is real value or just a different way of pricing the same capability?
We went through this exercise last year, and you’re right to be skeptical. The “400+ models” thing is accurate but misleading. You do get access to everything, but not everything costs the same internally.
What actually matters for TCO is which models you’re using. GPT-4 is more expensive than smaller models, but you’re not paying per-model in the quote—it’s bundled. So there’s some internal cost allocation that affects pricing tiers.
For our use case, we use maybe 4-5 models regularly. We pay for the bundle, so in theory we have access to 396 other models. But if we’re only using the same 4-5 that we were already paying for separately, the benefit of having access to 400 is mostly theoretical.
What mattered more was having everything in one place. The vendor negotiation was simpler, the contract renewal was simpler, the billing was simpler. That’s real value. But from a pure AI model cost perspective, we weren’t necessarily saving money, just organizing it differently.
The 400 models thing is real access, but your actual costs depend on usage-based pricing for heavier models. The base subscription gets you access, but if you’re running heavy workloads on expensive models, you still pay overage costs.
I’d recommend actually listing out which models you want to use, checking the pricing for each one, and comparing that to a consolidated subscription. Sometimes the consolidated approach wins, sometimes it doesn’t depending on your model mix.
For TCO comparison with Make/Zapier, you have to model scenarios. Don’t just look at base pricing. Calculate the cost to run your actual workflows on each platform, including any AI model costs. That’s the only comparison that matters.
The consolidated model does simplify procurement and reduces vendor management overhead, which has real value. But for pure model costs, you need to compare apples to apples by calculating your actual usage patterns.
If you’re doing high-volume processing with expensive models, the per-execution pricing on some platforms might win. If you’re doing moderate volume across varied models, consolidation might win. The 400 models itself is less relevant than the pricing structure for the models you actually use.
For enterprise TCO, I’d factor in three things: base subscription cost, overage/usage costs for your workflow patterns, and vendor management overhead. The third one almost never gets modeled but it’s often significant.
Fair question, and I appreciate you pushing back on the marketing language.
Here’s the reality: you get access to all 400+, but your pricing tier is based on execution volume, not on which models you use. A single subscription covers light usage of expensive models or heavy usage of cheaper models. You’re not paying per model, you’re paying based on how much you’re running things.
Where the value actually shows up in TCO is that you don’t have tiered licensing for different models. Compare this to Make or Zapier where you’re paying for platform operations PLUS separate fees if you want to add AI capabilities. We’ve rolled that into one number.
For your specific case, if you use 5-6 models regularly, the benefit is that you’re not managing 5-6 separate vendor relationships and bills. One contract, one invoice, one support channel. That overhead is real money when you’re at enterprise scale.
But yes, do the math on your actual usage. If you’re running low volume and your current AI model subscriptions are cheap, consolidation might not be a big win. If you’re managing complexity across multiple vendors and multiple AI model subscriptions, that’s where consolidation saves money by eliminating coordination overhead.