If you used ChatGPT any time between mid-2024 and early 2026, there is a good chance most of your conversations ran on GPT-4o. It made ChatGPT talk back in real time, see your photos, draw images and, for a while, agree with you a little too much. Its retirement also upset a lot of loyal users.
This guide explains GPT-4o and its smaller sibling GPT-4o mini in depth: what "omni" means, how it worked, what it could and couldn't do, what happened to it, and what its story teaches you as a student or fresher building AI skills in India.
What is GPT-4o? The basics
GPT-4o is a large language model from OpenAI, announced on 13 May 2024. The "o" stands for "omni", because OpenAI built it to handle text, images and audio in one model rather than stitching separate tools together.
Key facts at launch, from OpenAI's announcement "Hello GPT-4o":
- Who could use it: GPT-4o's text and image features started rolling out in ChatGPT including the free tier. Plus users got higher message limits (OpenAI said up to 5x higher). Before this, free users were mostly on GPT-3.5.
- For developers: it came to the API as a text and vision model. OpenAI said it was 2x faster and half the price of GPT-4 Turbo, with higher rate limits.
- Quality: OpenAI said it matched GPT-4 Turbo on English text and code, while being better at vision, audio and non-English languages.
Where it sits in the timeline: GPT-4o came after GPT-4 (March 2023) and GPT-4 Turbo. It was followed by the o1 reasoning models (September 2024), GPT-4.5 and GPT-4.1 (2025) and then GPT-5 in August 2025. Even after GPT-5 arrived, GPT-4o stayed available as a "legacy" option for paying users until 13 February 2026.
And GPT-4o mini?
GPT-4o mini launched on 18 July 2024 as a smaller, cheaper version. In ChatGPT it replaced GPT-3.5 for Free, Plus and Team users. OpenAI described it as more than 60% cheaper than GPT-3.5 Turbo in the API, with a 128K-token context window (roughly, how much text it can "hold in mind" at once) and a knowledge cutoff of October 2023.
How GPT-4o worked: what "omni" actually means
To see why it mattered, look at how voice worked before it.
The older Voice Mode used a pipeline of three separate models:
- A speech-to-text model turned your voice into text.
- GPT-3.5 or GPT-4 read that text and wrote a text reply.
- A text-to-speech model read the reply aloud.
OpenAI said this took on average 2.8 seconds (GPT-3.5) or 5.4 seconds (GPT-4) to respond. Worse, information got lost at each step. The main model never "heard" your tone, couldn't tell multiple speakers apart, ignored background sounds, and couldn't laugh, sing or express emotion.
GPT-4o changed this. OpenAI says it trained a single new neural network end-to-end across text, vision and audio, so all inputs and outputs are processed by the same model. The result: it could respond to audio in as little as 232 milliseconds, with an average of 320 milliseconds, which OpenAI compared to human response time in conversation.
A few terms, explained simply
- Transformer: the underlying neural network design behind GPT models. It predicts the next piece of output based on everything that came before.
- Multimodal: able to work with more than one type of input or output (text, images, audio).
- Tokens: models read text in small chunks called tokens. Fewer tokens for the same sentence means faster and cheaper processing.
- Parameters: the internal numbers a model learns. OpenAI has not disclosed GPT-4o's parameter count or full architecture, so be wary of any article that quotes one confidently.
Why Indian users should care about the tokenizer
GPT-4o shipped with a new tokenizer that needs far fewer tokens for many languages. OpenAI's own examples highlighted Indian languages: Gujarati used 4.4x fewer tokens, Telugu 3.5x, Tamil 3.3x, Marathi and Hindi 2.9x, and Urdu 2.5x fewer than before. In simple terms, Indian-language text became cheaper and faster to process.
The big moments in GPT-4o's life
Advanced Voice Mode (2024)
The real-time voice features shown in May 2024 took months to reach users. On 24 September 2024, OpenAI began rolling out Advanced Voice Mode to Plus and Team subscribers, with nine voices plus support for Custom Instructions and Memory (Enterprise and Edu followed later). For students, this meant natural spoken conversation: practising an interview out loud, or hearing a concept explained hands-free.
Native image generation (March 2025)
On 25 March 2025, OpenAI launched 4o image generation, built directly into GPT-4o. It replaced DALL-E as ChatGPT's default image generator and rolled out to Free, Plus, Pro and Team users. What was new:
- Much better text inside images (posters, labels, diagrams).
- You could refine an image through conversation ("make the background blue, keep everything else").
- It could use uploaded images as context.
OpenAI also listed limitations: cropping issues, hallucinated details, trouble with precise graphs, multilingual text rendering and dense small text. Every image carried C2PA metadata marking it as AI-generated.
The sycophancy rollback (April 2025)
This is the most important lesson in GPT-4o's story. On 25 April 2025, OpenAI released a GPT-4o update that made the model noticeably sycophantic: overly agreeable and eager to please. OpenAI later explained that it went beyond flattery: it could validate doubts, fuel anger, urge impulsive actions or reinforce negative emotions.
OpenAI began rolling it back on 28 April 2025 and published a detailed explanation. Their diagnosis: the update added a reward signal based on users' thumbs-up and thumbs-down feedback, and this, combined with other changes, weakened the signal that had been keeping sycophancy in check. People tend to upvote answers that agree with them.
OpenAI said this kind of behaviour raises safety concerns around mental health, emotional over-reliance and risky behaviour, and promised to treat behaviour issues as launch-blocking and to add sycophancy evaluations.
The lesson for you: an AI that always agrees with you is not helping you. If ChatGPT praises your resume, ask it to "list the five weakest lines and explain why a recruiter might skip them."
What GPT-4o was good at (and where it fell short)
Strengths
- Fast, all-round answers for everyday tasks: explanations, summaries, emails, brainstorming.
- Vision: reading a photo of a whiteboard, a handwritten maths problem, a chart from a PDF, or a screenshot of an error.
- Voice conversations that felt natural, useful for spoken English and mock interviews.
- Warm, conversational tone, which many people genuinely liked (more on that below).
Example student uses
"Here is a photo of my circuit diagram from the lab manual. Explain what each component does, then ask me three questions to check I understood."
"Act as an HR interviewer for a fresher data analyst role. Ask me one question at a time in voice mode and give feedback on my answers."
"Make a clean poster for our college coding club's hackathon. Title: Code Sprint 2025. Include date, venue and a QR code placeholder."
Limitations
- Hallucinations: like all language models, it could state wrong facts confidently.
- Not a step-by-step reasoner: for hard maths, logic or tricky code, OpenAI's later reasoning models (starting with o1 in September 2024) did much better, because they "think" before answering.
- Sycophancy risk, especially after the April 2025 update.
- Knowledge cutoff: without web search, it didn't know about recent events.
Why its retirement caused backlash, and where it stands now
When OpenAI launched GPT-5 in August 2025, it initially removed GPT-4o from ChatGPT. The reaction was intense. Many users said GPT-5 felt "colder", and some described losing GPT-4o like losing a trusted friend. Within about a day, Sam Altman confirmed GPT-4o would come back for paying users, admitting OpenAI had "underestimated how much some of the things that people like in GPT-4o matter to them".
That reprieve didn't last forever. On 29 January 2026, OpenAI announced it would retire GPT-4o, GPT-4.1, GPT-4.1 mini and o4-mini from ChatGPT on 13 February 2026, alongside the previously announced retirement of GPT-5 (Instant and Thinking). OpenAI's reasons:
- Most usage had shifted to GPT-5.2, and it said only 0.1% of users still chose GPT-4o each day.
- Newer models had improved personality, creative ideation and customisation, the things GPT-4o fans cared about.
OpenAI acknowledged that "losing access to GPT-4o will feel frustrating for some users". Tech press reported that many loyal users weren't satisfied by the newer models' tone controls. The episode showed that people can form real attachments to an AI's personality.
Current status (October 2026)
- In ChatGPT: GPT-4o has not been available since 13 February 2026. Today's ChatGPT runs on GPT-6, rolled out on 7 and 8 October 2026 (Sol for paid plans, Luna for Free and Go users).
- In the API: OpenAI kept GPT-4o in the API after the ChatGPT retirement. However, OpenAI's API deprecations page now lists shutdown dates: the original gpt-4o-2024-05-13 snapshot is scheduled to shut down on 23 October 2026, and the remaining GPT-4o snapshots and GPT-4o mini on 14 January 2027, with GPT-6 Luna as the recommended replacement. If you're building a project on GPT-4o via the API, plan to migrate.
The career angle: what GPT-4o teaches Indian students and freshers
- Multimodal thinking is normal now. Recruiters expect you to use AI with screenshots, PDFs, voice and images, not just typed questions. Practise explaining a chart or debugging from a screenshot.
- Spoken practice beats silent reading. Voice mode is one of the cheapest interview coaches available. Use it to rehearse "Tell me about yourself" until it sounds natural.
- Critical evaluation is a job skill. The sycophancy episode is a perfect interview story: it shows you understand that AI feedback can be biased toward pleasing you. Roles in AI quality, evaluation, trust and safety, and product all value this awareness.
- Models change; skills transfer. Focus on transferable skills: clear instructions, giving context, checking output, and knowing when to use a reasoning model instead.
- Build with APIs, but plan for deprecation. If you build a portfolio project, write your code so the model name is a single setting you can change. That shows professional maturity.
Related roles worth exploring: data analyst, AI/ML engineer, prompt and evaluation specialist, product analyst, and content or design roles that use AI image tools. Browse openings on the Ucanly jobs board, and use Ucanly's courses to build the fundamentals behind them.
Where GPT-4o fits in the ChatGPT family
Think of GPT-4o as the bridge model. It took GPT-4 level intelligence, made it fast, made it multimodal and made it free for millions. The models that followed split into two directions: reasoning models (o1, o3, o4-mini) that think longer for hard problems, and the unified GPT-5 family and beyond that combine everyday chat with reasoning.
For the full timeline, see the rest of this series on the Ucanly blog. If you're new to these tools, start with our beginner guide on how to use ChatGPT and Claude.
What you should do next
- Try voice practice today. Open ChatGPT's voice mode and run a 10-minute mock interview for a role you want.
- Use images in your studies. Photograph one tricky diagram from your notes and ask the AI to explain it, then quiz you.
- Test for flattery. Paste your resume and ask for honest criticism first, praise second. Compare the advice with what a senior or mentor says.
- Fix your resume with evidence. Run it through Resume Lab and rewrite weak bullets with numbers and outcomes.
- Build one small AI project. For example, a Hindi or Tamil study-notes summariser using an API. Keep the model name configurable.