ChatGPT 3.5 vs 4: What Actually Changed

1What Is the Difference Between GPT-3.5 and GPT-4?

GPT-4 is a later, more capable model than GPT-3.5, with the biggest practical improvements in reasoning through multi-step problems, following complex or nuanced instructions, and handling image input, which GPT-3.5 cannot do at all.

GPT-3.5 is not obsolete, though — it remains faster and cheaper to run, which makes it a reasonable choice for simple tasks where the extra reasoning power of GPT-4 is not needed.

2Reasoning and Accuracy

The clearest gap between the two models shows up on tasks that require holding several steps of reasoning in mind at once — a multi-part math problem, a coding bug that depends on understanding several functions together, or an instruction with several conditions attached.

On straightforward requests — summarizing a short paragraph, drafting a simple email, answering a basic factual question — the practical difference between the two models is far smaller.

3Handling Complex Instructions

GPT-4 is noticeably better at following prompts with several conditions or constraints at once — for example, an instruction that specifies tone, length, format, and a list of items to avoid all in a single request. GPT-3.5 is more likely to drop or partially ignore one of the constraints.

4Image Input

GPT-4 added the ability to accept images as part of a prompt, letting it describe a picture, read text in a photo, or answer questions about a chart or diagram. GPT-3.5 works with text only and has no equivalent capability.

5Speed and Cost

GPT-3.5 responds faster and is cheaper to run than GPT-4, which matters for applications sending a very high volume of requests or needing near-instant responses. That tradeoff — more reasoning power versus more speed and lower cost — is the practical reason GPT-3.5 has stayed relevant even after GPT-4's release.

• GPT-3.5: faster responses, lower cost, sufficient for simple drafting, lookup, and formatting tasks.
• GPT-4: slower and more expensive per response, but noticeably stronger on reasoning, complex instructions, and image understanding.

6Where Both Models Still Fall Short

Neither model is reliably accurate on every factual claim, and both can produce a confident, well-written answer that is simply wrong. This is especially true for niche facts, recent events, or precise numbers, where independent verification still matters regardless of which model produced the answer.

7Choosing the Right Model for a Task

The practical decision usually comes down to task complexity rather than a blanket preference for the newer model.

• Simple drafting, formatting, or lookup tasks: GPT-3.5 is usually fast enough and accurate enough.
• Multi-step reasoning, complex code, or nuanced writing with several constraints: GPT-4 is worth the extra time and cost.
• Any task involving an image: GPT-4 is required, since GPT-3.5 cannot process images at all.

8The Bigger Picture

Model generations continue to improve past both GPT-3.5 and GPT-4, but the underlying tradeoff this comparison illustrates — more reasoning depth versus more speed and lower cost — remains a useful lens for choosing between any two models, not just these specific ones.

Understanding this tradeoff, and how large language models actually work under the hood, is a foundational skill for anyone building applications on top of them.