So, OpenAI announced "Apps in ChatGPT," and there’s a lot of buzz. It feels a bit like the early days of the Apple App Store, doesn’t it? A whole new way for brands and services to interact with people. It’s easy to get excited about the possibilities, but if you’re running a business, that excitement probably comes with a big question mark: "What’s this actually going to cost?"
As it turns out, the answer isn’t a simple subscription fee. Building an "App in ChatGPT," or really any custom AI feature using OpenAI’s models, involves a tangle of costs, both obvious and hidden. This guide will walk you through the full picture of Apps in ChatGPT pricing, from the confusing pay-as-you-go API model to the development and upkeep expenses that often catch people off guard. We’ll give you a realistic idea of what to budget and show you how platform-based tools can give you a more predictable, and frankly, more sensible path to launching AI.
What are ‘Apps in ChatGPT’?
First, let’s get on the same page about what we’re talking about. "Apps in ChatGPT" is a new toolkit that allows brands to build small applications that work right inside the ChatGPT chat window. You can think of them as plugins. For instance, you could be talking to ChatGPT about a move, and an app from Zillow might pop up with property listings. Or you could ask it to whip up a workout playlist, and the Spotify app could build it for you right then and there.
This is definitely a new and interesting channel. But it’s different from what most businesses want to do, which is use OpenAI’s models to add AI features to their own products or internal tools. You might, for example, want an AI agent inside your helpdesk to answer customer tickets, or a chatbot on your website.
Even though the user sees something different, both of these projects, building an "App in ChatGPT" or adding AI to your own tools, use the same API pricing from OpenAI. And that’s where things get a little complicated.
The official OpenAI API model explained
To figure out the cost of building with OpenAI’s tech, you have to wrap your head around their API pricing. It’s not just a flat monthly fee.
Subscription plans vs. API access: A common mix-up
Let’s clear one thing up right away. A ChatGPT Plus or Business subscription is for people and teams who want to use the ChatGPT website for their own work. These plans get you faster responses and access to the newest models.
But, and this is important, these subscriptions do not give you the API access you need to build your own tools or "Apps in ChatGPT." For that, you need a totally separate, pay-as-you-go API account. It’s a different billing system entirely.
How the pay-as-you-go model works
OpenAI’s API pricing is based on something called "tokens." A token is just a piece of a word, roughly four characters of text. Every time you send a request to the API (your input) and every time you get a response back (the AI’s output), you use up tokens, and you get billed for every single one.
It’s kind of like those old cell phone plans where you paid for every text message you sent and received. Every word you type to the AI costs you money, and every word it sends back costs you money, too. To make it even more confusing, the price for input tokens (what you write) is different from the price for output tokens (what the AI writes back), and the output is almost always more expensive.
A breakdown of model costs
Not all AI models have the same price tag. The more powerful the model, the more you pay to use it. A tricky reasoning task that needs GPT-5 will cost a lot more than a simple sorting task you could give to a smaller, faster model.
Here’s a quick look at the pricing for some of OpenAI’s main models. You can see how much the costs can change.
| Model | Input Price (per 1M tokens) | Output Price (per 1M tokens) | Best For |
|---|---|---|---|
| GPT-5 | $1.250 | $10.000 | Complex, multi-step problems and coding. |
| GPT-5 mini | $0.250 | $2.000 | Faster, well-defined tasks. |
| GPT-5 nano | $0.050 | $0.400 | The fastest option for simple tasks like classification. |
| GPT-4.1 (Fine-tuning) | $3.00 | $12.00 | Customizing the model for specific use cases. |
(Source: OpenAI API Pricing)
The unpredictability problem
Your customer support volume can swing wildly from one month to the next. A simple question like "Where’s my order?" might only cost a tiny fraction of a cent. But a long, complicated troubleshooting chat could burn through thousands of tokens and cost 10 or 20 times more. You can’t predict what kind of question is coming next, which means your monthly AI bill could be $500 one month and jump to $5,000 the next. That kind of financial guesswork is a big risk for any business and a major reason why many companies start looking for options with more stable costs.
The hidden costs: Why API fees are just the beginning
If the unpredictable API bill wasn’t enough to worry about, it’s really just the start. The total cost of a do-it-yourself AI project gets much, much higher once you start adding in development, infrastructure, and maintenance.
Development and integration costs
First off, you need someone to actually build this thing. This isn’t a task for a junior developer. It takes specialized AI engineers who understand how to work with large language models, and those engineers are in high demand and have the salaries to match.
On top of the core programming, you also have to pay for designing the user experience, building the server logic to handle API calls securely, and managing sensitive API keys. Based on what we see in the industry, a medium-sized AI app integration can easily cost $30,000, $80,000 just for the initial development, and that’s before you’ve paid a single dollar in API fees.
Infrastructure and hosting costs
Your AI tool needs a server to run on. That means setting up and paying for cloud servers on a platform like AWS or Google Cloud to manage all the back-and-forth with the API. Depending on how much it’s used, this can add another $500 to $3,000 per month to your bills. You’ll also need to pay for database storage to log conversations and make sure your system doesn’t crash if you get a sudden rush of users.
Ongoing maintenance and optimization
An AI integration isn’t something you can just build and then forget about. It’s a living system that needs constant attention. Your team will need to:
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Keep an eye on performance and costs: Someone has to watch your API usage closely to make sure costs don’t get out of hand.
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Tweak your prompts: The instructions you give the AI (your prompts) need to be constantly refined to get better, more accurate answers and hopefully use fewer tokens.
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Stay on top of model updates: OpenAI is always releasing new models. Every time they do, your code might break or need adjustments to work with the new version.
All of this adds up to a lot of ongoing work that keeps your most expensive engineers busy with upkeep instead of building new things.
A better way: The platform approach to avoid complex pricing
When you look at all the complexity and cost of a DIY approach, it’s pretty clear why so many businesses are choosing AI platforms instead. Tools built for specific jobs, like customer support, handle all the technical heavy lifting for you. This lets you get the good parts of AI without all the headaches.
Get predictable pricing and a clear ROI
The first and biggest win of using a platform is ditching that volatile, token-based pricing. Instead of a bill that looks like a rollercoaster, you get a stable, predictable monthly cost.
This is where a platform like eesel AI really helps. eesel AI offers straightforward, fixed monthly plans based on the features you need. Most importantly, there are no per-resolution fees. This means your bill doesn’t suddenly explode just because you had a busy month with lots of customer questions. This predictability makes it easy to budget for AI and actually figure out if you’re getting a good return on your investment.
A screenshot of eesel AI's pricing page, showing the predictable, fixed monthly plans that contrast with volatile Apps in ChatGPT pricing.Go live in minutes, not months
A DIY project can take months of expensive engineering time before you see any results. With a platform, you can be up and running in a tiny fraction of that time.
With a tool like eesel AI, you can connect your helpdesk, whether it’s Zendesk or Freshdesk, with simple one-click integrations. It’s designed to be self-serve, so you can set everything up yourself in a few minutes without having to schedule a sales call or sit through a long onboarding. You can immediately pull in knowledge from all your company’s sources, like docs in Confluence, past support tickets, or internal wikis.
This image displays the variety of one-click integrations available in eesel AI, simplifying the setup process compared to the complex integration needs of custom Apps in ChatGPT pricing models.Get total control without the technical mess
A common worry about platforms is that they might be too rigid and won’t fit your company’s unique needs. But modern platforms are built to be flexible.
For example, eesel AI gives you a fully customizable workflow builder. You can define your AI’s personality and tone of voice, pick exactly which kinds of tickets you want it to handle, and even create custom actions that let it do things like look up order information or update ticket statuses.
A view of the eesel AI platform where users can set up custom rules and guardrails, demonstrating the control available without the high technical overhead associated with Apps in ChatGPT pricing.Best of all, you can try it all out without any risk. eesel AI has a powerful simulation mode that lets you test your entire AI setup on thousands of your past support tickets. You can see exactly how it would have answered, get accurate predictions on how many tickets it will solve, and calculate your potential savings before you ever turn it on for your customers. That’s a level of confidence and control that’s just about impossible to get when you build from scratch.
The eesel AI simulation mode dashboard, which allows businesses to test their AI setup and forecast ROI, a key advantage over the unpredictable nature of Apps in ChatGPT pricing.Apps in ChatGPT pricing: Making the right choice for your business
The real cost of "Apps in ChatGPT" or any custom OpenAI project goes way beyond the price per token. When you add up the confusing API fees, the high costs of development and servers, and the constant maintenance work, it becomes a very big investment of both time and money.
Going the DIY route gives you complete flexibility, but it comes with high costs, unpredictable bills, and a long wait before you see any value. For most businesses, a platform is simply the smarter way to go. It takes the risk out of the investment with predictable pricing, fast setup, and powerful controls that are easy to use, all without needing to hire a team of AI engineers.
Next steps
If you’re looking to use AI for customer support without the budget surprises and engineering headaches, the best next step is to check out a platform built for that purpose.
See how eesel AI provides a powerful, predictable, and easy-to-launch AI agent for your support team. Start your free trial today.
Frequently asked questions
A ChatGPT Plus or Business subscription allows individuals and teams to use the ChatGPT website for their own work. However, Apps in ChatGPT pricing, which refers to building custom AI tools, requires a separate pay-as-you-go API account. These are distinct billing systems for different purposes.
The OpenAI API model bills you based on "tokens," which are pieces of words, for both your input and the AI’s output. Every interaction with the AI consumes tokens, and you’re charged per token, with output tokens generally being more expensive.
Budgeting is challenging because user activity and interaction length are unpredictable. A simple query might cost very little, while a complex, lengthy conversation could consume many more tokens, leading to wildly fluctuating monthly costs.
Beyond API token fees, significant hidden costs include specialized AI development and integration expenses (e.g., $30,000, $80,000 for initial build), infrastructure and hosting (e.g., $500, $3,000/month), and ongoing maintenance for performance monitoring, prompt tuning, and model updates.
Yes, different AI models have varying price tags; more powerful models like GPT-5 are significantly more expensive per token than simpler ones like GPT-5 nano. Choosing the right model depends on the complexity of the task, balancing cost with required reasoning capabilities.
Yes, using a specialized AI platform like eesel AI offers predictable, fixed monthly plans instead of volatile token-based billing. These platforms handle the technical complexities and often include features that make budgeting and ROI calculation much clearer.
