GPT-4 Turbo vs GPT-4: A practical guide to what’s changed

If you feel like you can't keep up with OpenAI's new AI models, you're not alone. The jump from GPT-4 to GPT-4 Turbo came with big promises: faster speeds, lower costs, and more up-to-date knowledge. But since its release, the reviews have been a mixed bag. So, is the newer "Turbo" version always the better choice?

This guide is here to clear things up. We'll get into the real-world differences between GPT-4 and GPT-4 Turbo, covering everything from performance and price to their core abilities. And more importantly, we’ll talk about why for business uses like customer support, the platform you use to manage these models matters more than the models themselves.

A quick refresh on GPT-4

When GPT-4 launched in March 2023, it was a pretty big deal. It was a huge step up from GPT-3.5 and quickly became the model to beat. It was impressive because it could handle complex reasoning, generate accurate text, and follow instructions with a lot more nuance than people were used to. For the first time, an AI model felt like a genuinely helpful collaborator.

It was trained on a huge amount of data, but its knowledge famously stopped in September 2021, so you couldn't ask it about recent events. It also had an 8,000-token context window, which is like having a short-term memory of about 24 pages. While powerful, it was also a bit slow and expensive to run on a large scale, which left the door open for something more efficient.

Understanding GPT-4 Turbo

OpenAI released GPT-4 Turbo in November 2023, directly responding to everyone asking for better performance and lower costs. It was built to be a faster, smarter, and cheaper version of the original.

It arrived with a few major upgrades:

1. More recent knowledge: Its training data goes up to April 2023, making its answers much more useful for current topics.

2. A massive context window: The context window ballooned to 128,000 tokens. That's like being able to process a 300-page book in one go, allowing it to analyze much larger documents and conversations.

3. A lower price tag: It was launched at a much lower price, making it more accessible for businesses and developers wanting to build apps with it.

On top of that, GPT-4 Turbo was built to handle more than just text. It can accept image inputs and has some pretty advanced text-to-speech features.

A head-to-head comparison

While the specs make Turbo look like the obvious winner, the reality is a little more complicated. Let's break down the practical differences you'll notice when using them.

Performance, speed, and the 'laziness' debate

One of Turbo's main selling points is its speed. It generates responses much faster, which is essential for anything happening in real-time, like a customer support chatbot. But it seems this speed might come at a cost.

If you've spent any time on developer forums or Reddit, you've probably seen the complaints that GPT-4 Turbo can be 'lazy.'

Reddit

It sometimes gives shorter, less detailed answers or just refuses to complete a complex task that the original GPT-4 would have tackled. This is likely a side effect of OpenAI optimizing for speed and cost, but it can be annoying when you need a thorough answer.

Knowledge cutoff and context window

This is where the differences are crystal clear. GPT-4 knows nothing past September 2021, while GPT-4 Turbo is up-to-date as of April 2023. If what you're working on requires information about recent events, new products, or current affairs, Turbo is really your only option here.

The context window gap is even bigger. With 128k tokens, GPT-4 Turbo can process a huge amount of information at once. Think about feeding it an entire codebase, a long legal contract, or a full day's worth of customer support chats. The original GPT-4's 8k window, which seemed huge at the time, feels pretty small by comparison for these kinds of tasks.

Core capabilities and multimodality

OpenAI also says that GPT-4 Turbo is better at following specific instructions, especially when you need a structured output. For example, you can tell it to "always respond in JSON format," and it will actually listen. This is a huge relief for developers because it means less time spent cleaning up messy outputs.

Turbo also brings true multimodality to the table. While both models can connect to DALL-E 3 to create images, GPT-4 Turbo can directly analyze images you give it. You can ask it to describe a photo, make sense of a chart, or pull text from a picture. This, along with its text-to-speech function, makes a whole new world of applications possible.

The all-important factor: Pricing

For any business, cost is a huge deal. GPT-4 Turbo was designed from the ground up to be more affordable.

• Input tokens (what you send to the model) are about 3x cheaper.

• Output tokens (what the model sends back) are 2x cheaper.

This price drop means businesses can actually afford to use top-tier AI for high-volume jobs, like running customer service bots or generating content, without their budget spiraling out of control.

Why the platform matters more than the model

If you rely directly on the model's API, you’re stuck with its quirks (like the "laziness" problem), you'll need months of developer time to build and manage it, and you have no good way to test its behavior safely.

This is exactly where a specialized platform like eesel AI steps in. It's designed to handle these problems so you have full control over how AI works for your team.

Handle inconsistency

With eesel AI’s workflow engine and prompt editor, you can set the AI's exact tone and give it very specific instructions. If a model is being too brief, you can tell it to be more thorough, helping you work around the base model's default settings.

Test before you launch

Don't just hope your AI will work. With eesel AI, you can run a simulation on thousands of your past support tickets. You get an accurate preview of your automation rate and can check every single AI response before it ever talks to a customer.

Connect your knowledge instantly

A raw model has no idea what your business is about. eesel AI connects to all your company's knowledge, whether it's in past Zendesk tickets, articles in Confluence, or guides in Google Docs. It learns your specific context automatically, so its answers are always personalized and accurate.

Go live in minutes, not months

Forget waiting for sales demos or dealing with a complicated setup. You can connect your helpdesk and launch a working AI agent in minutes, all on your own.

Choosing the right model for your business

So, when it comes down to a GPT-4 Turbo vs GPT-4 comparison, Turbo is the more practical choice for most businesses. It's much faster, way cheaper, has a massive context window, and knows what’s happened in the world since 2021. While some people still prefer the original GPT-4 for its detailed responses on certain complex tasks, Turbo’s overall advantages are hard to ignore for day-to-day business use.

But the real takeaway isn't about picking one "best" model. It's realizing that the true power of AI for your business comes from the platform that puts you in control. A system that lets you test, customize, and safely deploy AI is far more valuable than the small differences between the models themselves.

Instead of getting lost in the model debate, why not explore a platform that lets you build with confidence? See how eesel AI can help you take control of your customer support AI.