GPT-3.5 Explained: The Model That Launched ChatGPT, How RLHF Worked and Why It Was Retired (2026 Guide)

When ChatGPT appeared on 30 November 2022, most people had never heard the name "GPT-3.5". Yet that model is the reason the world suddenly started talking to computers in plain language. It was the engine inside the very first version of ChatGPT, and for almost two years it was the model every free user talked to.

In this part of our "ChatGPT models explained" series, we go deep on GPT-3.5: where it came from, how it was trained, what it could and couldn't do, why it was replaced, and what its story teaches you as a student or fresher building a career in an AI-shaped job market.

What exactly was GPT-3.5?

GPT-3.5 is not one single model. It is OpenAI's name for a series of models built on top of GPT-3 during 2022. The family included models with names like code-davinci-002, text-davinci-002 and text-davinci-003, which developers used through OpenAI's API, and later gpt-3.5-turbo, the chat-optimised version.

The key line comes from OpenAI's own launch post for ChatGPT, dated 30 November 2022: ChatGPT was "fine-tuned from a model in the GPT-3.5 series, which finished training in early 2022." OpenAI also described ChatGPT as a "sibling model to InstructGPT", which was trained to follow instructions in a prompt and give detailed responses.

A quick word on the name. GPT stands for Generative Pre-trained Transformer:

• Generative: it produces new text, one small piece (a "token") at a time.
• Pre-trained: it first learns general language patterns from a very large amount of text before being shaped for any specific job.
• Transformer: the neural network design, introduced by Google researchers in 2017, that lets the model weigh how every word in your message relates to every other word.

How big was GPT-3.5? OpenAI has not disclosed its parameter count. You will see confident numbers online, but they are guesses. The original GPT-3 (2020) had 175 billion parameters according to OpenAI's paper, but the sizes of the GPT-3.5 models were never officially published.

Where GPT-3.5 sits in the ChatGPT timeline

Here is the short history, with dates from OpenAI's own announcements:

• 2020: GPT-3. A powerful text generator, but you had to coax it with clever prompts. Ask it a question and it might continue your text instead of answering.
• 27 January 2022: InstructGPT. OpenAI published models trained to follow instructions, and made them the default models in its API.
• Early 2022: the GPT-3.5 model that ChatGPT would be built on finished training.
• 30 November 2022: ChatGPT launches as a free "research preview", powered by a GPT-3.5 model.
• 1 February 2023: ChatGPT Plus launches as a paid plan, initially offering access during peak times, faster responses and early access to features.
• 1 March 2023: the ChatGPT API. OpenAI released gpt-3.5-turbo to developers, saying it was "the same model used in the ChatGPT product" and "10x cheaper than our existing GPT-3.5 models."
• 14 March 2023: GPT-4 arrives for Plus users, while GPT-3.5 stays the free default.
• 18 July 2024: GPT-4o mini replaces GPT-3.5. OpenAI said Free, Plus and Team users could use GPT-4o mini "in place of GPT-3.5" from that day, with Enterprise users following the next week.

So GPT-3.5 was the model that introduced ChatGPT to the world, and the one most free users relied on for about 20 months.

How GPT-3.5 learned to chat: InstructGPT and RLHF explained

The big idea behind GPT-3.5 in ChatGPT is not a bigger brain. It is better training on human preferences. The technique is called Reinforcement Learning from Human Feedback (RLHF), and OpenAI said ChatGPT was trained using the same methods as InstructGPT, with some differences in how the data was collected.

OpenAI's InstructGPT post describes three steps. In plain English:

1. Show it good examples (supervised fine-tuning). Human trainers wrote examples of the kind of answer they wanted for real prompts. The model was trained to imitate these.
2. Teach a "judge" what humans prefer (reward model). The model wrote several answers to the same prompt, and humans ranked them from best to worst. A separate model, the reward model, learned to predict which answers people would prefer.
3. Practise against the judge (reinforcement learning). The main model was fine-tuned with an algorithm called PPO to produce answers that the reward model would score highly.

The result surprised many people. In OpenAI's InstructGPT study, human labelers preferred answers from a 1.3 billion parameter InstructGPT model over answers from the 175 billion parameter GPT-3, even though the smaller model had more than 100 times fewer parameters. Training on human feedback made the model far more useful without simply making it bigger.

For ChatGPT, OpenAI added dialogue: trainers played both the user and the AI assistant, so the model learned to handle back-and-forth conversation, follow-up questions and corrections.

What changed with GPT-3.5 Turbo

When gpt-3.5-turbo arrived in the API in March 2023, it introduced a chat format. Instead of sending one long block of text, developers sent a list of messages, each marked as coming from the "system", the "user" or the "assistant". OpenAI called the underlying format Chat Markup Language (ChatML). This is still the basic pattern used by most AI chat apps you might build today.

Later versions improved it further. At OpenAI DevDay on 6 November 2023, OpenAI announced a GPT-3.5 Turbo version with a 16K token context window by default. A "token" is a chunk of text, roughly part of a word, and the context window is how much text the model can consider at once, including your message, the conversation so far and its own reply.

What GPT-3.5 could do, and where it fell short

Strengths, with examples for students

For its time, GPT-3.5 felt magical. As a student, you could:

• Get a concept explained in simple language, then ask for a simpler version, an analogy or an example.

Explain the difference between TCP and UDP to a second-year student, using a WhatsApp call and a file download as examples.

• Draft and rewrite text: emails, cover letters, statements of purpose and summaries.
• Write and explain code in common languages like Python, Java, C++ and JavaScript, and help you understand error messages.
• Generate practice questions and quiz you on a topic.
• Brainstorm project ideas, outlines and test cases.

It was also fast, which is why OpenAI used the word "Turbo". Many students in India got their first taste of AI-assisted learning through free GPT-3.5 in ChatGPT.

The limitations you should understand

OpenAI's own launch post listed the problems honestly, and they are worth knowing because some still apply to every AI model:

• Plausible but wrong answers. OpenAI said ChatGPT "sometimes writes plausible-sounding but incorrect or nonsensical answers." This is often called hallucination.
• Sensitive to wording. A small change in how you asked a question could flip the answer from "I don't know" to a correct reply, or the other way round.
• Too wordy. It often repeated phrases and over-explained.
• Guessing instead of asking. For an unclear question, it usually guessed what you meant rather than asking a clarifying question.
• Imperfect safety. It could sometimes respond to harmful instructions or show bias, despite OpenAI's efforts.

There were practical limits too:

• No live knowledge at launch. It learned from data up to a cut-off date and could not browse the web in its first version, so it could be out of date about recent events.
• Text only at launch. You could not upload a photo of your notebook or a PDF in the original ChatGPT.
• Weaker reasoning than later models. Multi-step maths, tricky logic and long documents were where it stumbled most. GPT-4, released a few months later, was noticeably stronger here.

Lesson for you: always verify facts, numbers, dates and citations an AI gives you. That habit started with GPT-3.5 and it still matters today.

Current status of GPT-3.5 (October 2026)

• In ChatGPT: GPT-3.5 has not been part of ChatGPT since 18 July 2024, when OpenAI replaced it with GPT-4o mini. The ChatGPT you use today runs on much newer models: GPT-6, rolled out on 7 and 8 October 2026, with variants called Sol for paid plans and Luna for Free and Go users.
• In the API: OpenAI's deprecations page lists gpt-3.5-turbo and gpt-3.5-turbo-0125 (along with fine-tuned GPT-3.5 Turbo models) with a shutdown date of 23 October 2026, announced on 22 April 2026. Older snapshots like gpt-3.5-turbo-0613 were shut down earlier. If you follow an old tutorial that uses gpt-3.5-turbo, switch to a current model listed in OpenAI's documentation.

In other words, GPT-3.5 is now history. But it is very important history.

Career lessons from the GPT-3.5 story

GPT-3.5 teaches a few things that are directly useful for your career:

• Training approach can matter as much as size. The InstructGPT result showed that a smaller model trained with human feedback beat a much bigger one. In your own learning, how you practise matters more than how many hours you log.
• The "chat messages" pattern is a real skill. If you want to build AI projects, learn how the system, user and assistant message structure works. It shows up in almost every AI API.
• Human feedback is a job, not just a technique. RLHF needs people who write examples, rate answers and check quality. Roles like AI trainer, data annotator, evaluation specialist and prompt or content quality reviewer grew out of this approach, alongside engineering roles in machine learning and MLOps.
• Verification is a career skill. Employers value people who can use AI quickly and also spot when it is wrong.

Projects you could build to show these skills:

• A doubt-solving bot for one subject, using any current chat API and the system/user/assistant format.
• A comparison report where you ask the same 20 questions to two models and score them for accuracy, a small version of the evaluation work AI teams do.
• A resume bullet improver that only rephrases facts you provide.

When you add such projects to your resume, describe what you built and what you learned, not just "used ChatGPT". You can check how your project bullets read with the Ucanly AI resume review.

Where GPT-3.5 fits in the ChatGPT family

Think of GPT-3.5 as the first chapter of ChatGPT. It came after GPT-3 and InstructGPT, launched ChatGPT itself, and was followed by GPT-4 (March 2023), GPT-4o (May 2024) and GPT-4o mini (July 2024), which took over its job for free users. Everything since, from reasoning models to GPT-5 and GPT-6, builds on the same idea of making a pre-trained model more helpful through human feedback.

Read the rest of this series on the Ucanly blog, and if you are just starting out, read our beginner guide on how to use ChatGPT and Claude.

What you should do next

1. Read the original sources. Open OpenAI's "Introducing ChatGPT" (30 November 2022) and "Aligning language models to follow instructions" (InstructGPT) posts. They are short and readable.
2. Draw the RLHF pipeline from memory: examples, rankings, reward model, reinforcement learning. If you can explain it in an interview, you stand out.
3. Try the chat message format with any current AI API or playground, using a system message to set the role.
4. Run a mini evaluation: ask an AI ten questions from your syllabus and check every answer against your textbook.
5. Build one small project from the list above and put it on GitHub with a clear README.
6. Pick a structured learning path in AI, data or development from our courses, so your skills keep pace with the models.

GPT-3.5 is retired, but the skills it made valuable, asking clearly, checking carefully and building with AI, are only getting more important.