GPTs vs Assistants API vs AgentKit: Which Is Best for AI Agents?

So, OpenAI has rolled out a few different tools for building AI agents, but with names like GPTs, Assistants API, and AgentKit, it’s easy to feel like you need a glossary just to get started.

Picking the wrong tool isn't just a small hiccup. It can lead to months of wasted development time. Or even worse, you could end up with a slick AI agent that can’t actually connect to your core business systems, like your helpdesk. You might build a brilliant bot that can't do anything genuinely useful for your customers or your team.

This guide will clear things up. We'll walk through:

• A straightforward explanation of what Custom GPTs, the Assistants API, and AgentKit are.

• A direct comparison of their best use cases, how much you can customize them, and how they’re deployed.

• A transparent look at their very different pricing models, so you know what you’re getting into.

GPTs vs Assistants API vs AgentKit: What are OpenAI's agent-building tools?

Choosing the right foundation for your AI agent begins with understanding what each tool was built for. They all use OpenAI's models under the hood, but they solve very different problems for different people.

What are Custom GPTs?

Custom GPTs are basically personalized versions of ChatGPT that you can create without writing any code. You can give them specific instructions, a unique personality, and even upload knowledge files for them to reference. Think of it as creating your own mini-expert version of ChatGPT for a niche topic you care about.

They're mainly for individuals, hobbyists, and non-technical folks who want to whip up simple, specialized chatbots for personal use or small internal team experiments.

The biggest catch? They are designed to live exclusively inside the ChatGPT world. This makes it a real headache to integrate them directly into external business tools like Zendesk or Slack, which pretty much takes them out of the running for serious, automated customer support.

What is the Assistants API?

The Assistants API is a framework for developers to build AI agents that can remember conversations right into their own applications. This is the toolkit for serious, custom AI development. It handles conversation history (called threads), allows for tools like Code Interpreter and Retrieval, and supports function calling, which lets the AI interact with other systems.

This one is purely for developers and engineering teams who have the time and resources to build and maintain custom AI applications from the ground up.

Its main downside is the steep learning curve and the sheer amount of engineering work involved. Building a production-ready support agent with the Assistants API isn't a weekend project; it's a months-long endeavor that involves a lot of coding, testing, and managing infrastructure.

What is AgentKit?

AgentKit is OpenAI's newest offering, designed to make it a bit easier to build, deploy, and fine-tune agents for business needs. It bundles a few things together:

• Agent Builder: A visual, drag-and-drop canvas for mapping out how your agent should behave.

• ChatKit: A library of ready-made UI components to help you put a chat interface on your website.

• Evals: Tools for testing your agent to see how well it's performing.

AgentKit is aimed at product teams and developers inside larger companies who want a more structured, faster way to build agents.

But here’s the fine print: while the Agent Builder is visual, getting the final product live still requires a developer. You'll need someone to set up a server, handle the integration, and manage the backend. It simplifies the logic-building part but doesn't remove the need for an engineer to get it across the finish line.

This chart shows how AgentKit's components like Agent Builder and ChatKit work together, providing a visual overview in the GPTs vs Assistants API vs AgentKit comparison.

GPTs vs Assistants API vs AgentKit: Key differences

Alright, now that we have a handle on what they are, let's put them side-by-side and look at the things that really matter to a business: practical uses, level of control, and how they play with the tools you already use.

Use cases and target audience

• Custom GPTs: Best for a personal productivity hack, an internal info-bot for your team that you can share with a link, or a fun side project. They just aren't built for customer support that needs to scale.

• Assistants API: The right choice when you need to embed a deeply customized AI assistant inside your own software, like a "coding copilot" in a development environment or a "data analyst" inside a business intelligence dashboard. It's often way more complex than what’s needed for most support automation.

• AgentKit: Geared toward building more polished, customer-facing agents, like a chatbot on your website for sales questions or a more advanced internal helpdesk assistant. It's a step closer to a business solution, but it still needs a technical push to go live.

• The business-ready alternative: Let's be real. Most support teams need a powerful AI agent live in their helpdesk this week, not next quarter. This is where a purpose-built platform comes in. A solution like eesel AI is designed to close that gap. It integrates directly into Zendesk, Freshdesk, and Intercom in minutes, giving you a ready-to-go agent without the development marathon.

Customization, control, and workflow

• Custom GPTs: You get very little control here. The agent's logic is mostly a black box, driven by a single prompt and whatever files you upload. You can't design multi-step workflows or complex if/then logic.

• Assistants API: This gives you total control, but you have to build every last piece of it in code. Developers are on the hook for managing the state, logic, and tool calls. You have all the power, but you also have all the responsibility.

• AgentKit: The Agent Builder provides good visual control over the workflow with if/then logic nodes. But if you want to create custom actions to connect to your business systems (like checking an order status in Shopify), you'll still need a developer to write that part.

• Putting you in the driver's seat: This is where a dedicated platform really makes a difference. With eesel AI's workflow engine, non-technical users get to call the shots. You can use a simple prompt editor to define the AI's personality, choose exactly which tickets it handles, and set up powerful custom actions. Plus, you can test it all risk-free in a simulation mode before it ever talks to a real customer.

Deployment and integration

• Custom GPTs: They live almost entirely within the ChatGPT interface and are shared via a direct link. There’s no straightforward way to embed them in your helpdesk or on your website.

• Assistants API: Your engineering team has to build the entire user interface and backend infrastructure to host and run the agent within your application.

• AgentKit: ChatKit gives you some pre-built UI components, but a developer still has to integrate them into your website, set up a server, and manage all the API communication. It's not a simple copy-and-paste job.

• The one-click solution: This implementation hassle is a major roadblock for most support teams. In contrast, eesel AI was designed for instant integration. With one-click connections to major help desks and chat tools, you can be live in minutes, not months, without having to pull engineers off your main product.

Understanding the pricing models

Cost is a huge factor, and the pricing for these tools is all over the place. It's really important to get how you'll be billed to avoid any nasty surprises down the line.

Custom GPTs pricing

The cost for Custom GPTs is tied to a ChatGPT subscription. You need a paid plan just to make and use them.

• Model: Flat monthly subscription fee.

• Cost:

  • ChatGPT Plus: $20 per month for individuals.

  • ChatGPT Business: $25 per user/month (billed annually).

• Takeaway: This model works for individuals or small teams. It doesn't really scale for business use cases where you're dealing with hundreds or thousands of customer chats.

Assistants API and AgentKit pricing

Both the Assistants API and AgentKit operate on a purely usage-based model. You get charged for the processing power (tokens) your agent uses. AgentKit itself doesn't have a platform fee; you just pay for the underlying API calls it triggers.

• Model: Pay-as-you-go, per token.

• Cost: The price is based on how many tokens you use, and it varies depending on the AI model. A complex agent that needs to reason through multiple steps or pull information from documents will burn through far more tokens (and cost a lot more) than a simple Q&A bot.

• Takeaway: The biggest challenge here is unpredictable costs. Your monthly bill can swing wildly depending on how many customers contact you, making it incredibly difficult to budget. You pay for every test run, every customer chat, and every "thinking" step the model takes.

A screenshot of the usage-based pricing for OpenAI's API, which applies to both AgentKit and the Assistants API, highlighting a key consideration in the GPTs vs Assistants API vs AgentKit choice.

The eesel AI alternative: Predictable and transparent

For a business, being able to predict your budget is non-negotiable. eesel AI offers a transparent pricing model built for support teams.

The main benefit here is there are no per-resolution fees. Our plans are based on a fixed number of monthly AI interactions, so you'll never be shocked by a huge bill after a busy month. All our core products (AI Agent, Copilot, Triage, and more) are included in one simple price.

Plan	Monthly (bill monthly)	Effective /mo Annual	AI Interactions/mo
Team	$299	$239	Up to 1,000
Business	$799	$639	Up to 3,000
Custom	Contact Sales	Custom	Unlimited

This approach removes the financial risk and budget headaches that come with usage-based API pricing, letting you scale your support automation confidently.

Which OpenAI tool is right for you? A summary table

Feature	Custom GPTs	Assistants API	AgentKit
Target Audience	Individuals, Non-technical users	Developers, Engineers	Product Teams, Developers
Technical Skill	None	Expert (Coding Required)	Moderate (Dev Required for Deploy)
Primary Use Case	Personal productivity, Simple bots	Custom in-app assistants	Customer-facing web chatbots
Customization	Low (Single Prompt)	High (Code-based)	Medium (Visual Workflow)
Deployment	Inside ChatGPT	Your own application	Embedded on your website
Pricing Model	Flat Subscription	Usage-based (Per Token)	Usage-based (Per Token)

Moving from developer tools to business solutions

OpenAI has given us an incredible set of building blocks for AI agents. Custom GPTs are great for personal projects, the Assistants API offers unlimited power for deep, code-intensive work, and AgentKit gives teams with developers a more streamlined toolkit.

But they all have one thing in in common: they are developer tools, not complete business solutions. If you're a Head of Support or a CX leader, your goal isn't to build an agent from scratch; it's to solve customer problems faster, shrink your ticket backlog, and make your team's life easier. These tools are like the raw ingredients, but you still have to find a recipe, get the other groceries, and cook the meal yourself.

This is where a solution like eesel AI fits in. We take the power of these advanced models and package them into a platform that's built for the realities of customer support. We handle the tricky integrations, provide a truly no-code workflow editor, and offer a predictable price so you can focus on what actually matters: delivering a great customer experience.

Ready to deploy a powerful AI agent without the development headache? Try eesel AI for free and see how you can automate your support in minutes, not months.