Key Takeaways
- The performance jump. Launched on March 14, 2023, GPT-4 scored in the top 10% on a simulated bar exam, entirely reversing GPT-3.5’s bottom 10% result.
- The multimodal shift. GPT-4 was OpenAI’s first flagship model to process images alongside text. GPT-3.5 was strictly text-only.
- Context window expansion. GPT-3.5 Turbo handled 4,096 tokens before upgrading to 16,385.
- End of life for GPT-4. OpenAI retired GPT-4o, GPT-4.1, and GPT-4.1 mini from ChatGPT on February 13, 2026.
- The current lineup. The GPT-5 family is the active standard. OpenAI launched the GPT-5.6 preview on June 27, 2026, and recommends migrating all workloads to this new architecture.
- Legacy use persists. Orca Security found GPT-4o still present in 37.6% of AI-adopting cloud environments it studied, more than any newer OpenAI model.
Even today, many people search for ChatGPT 3, GPT-3 vs GPT-4, or ChatGPT 3.5 vs 4 when they mean the free version of ChatGPT that originally ran on the GPT-3.5 model. This guide explains the practical differences between ChatGPT 3.5 vs 4, including capabilities, benchmarks, availability, and what replaced them.
It covers the difference between ChatGPT 3.5 and 4 in full, from published scores to what each model could actually do. It also answers the question most comparisons skip: whether either is still available to use. The short answer is that GPT-4 is gone from ChatGPT and the API versions are on their way out.
GPT-3 vs GPT-3.5 vs GPT-4: Understanding the Names
Most comparisons treat GPT-3 and GPT-3.5 as the same thing. They are not, and the distinction explains why so many searches for ChatGPT 3 land on the wrong answer.
GPT-3 launched in June 2020 with 175 billion parameters. Its best-known model was davinci. It was an API product for developers, and it never powered ChatGPT.
GPT-3.5 arrived in late 2022 as a fine-tuned successor. text-davinci-003 shipped in November 2022, and ChatGPT launched on a model from this family on November 30, 2022. This is the model almost everyone means when they say GPT-3.
GPT-4 followed on March 14, 2023, as a separate generation with a different architecture and multimodal input.
GPT-3.5 vs GPT-4: Full Comparison Table
This ChatGPT 3 vs 4 comparison highlights the practical differences that actually mattered to developers. It covers the same ground people search for in GPT-3.5 vs GPT-4, from reasoning to availability.
| GPT-3.5 | GPT-4 | |
|---|---|---|
| Released | text-davinci-003 November 2022, ChatGPT launch November 30, 2022, gpt-3.5-turbo API March 2023 | March 14, 2023 |
| Reasoning | Handled straightforward tasks well, struggled with multi-step logic | Noticeably stronger on multi-step reasoning and nuanced instructions |
| Simulated bar exam | Bottom 10% of test takers | Top 10% of test takers |
| MMLU benchmark | Around 70% | 86.4% |
| Multimodality | Text only | Text and image input, text output |
| Context window | 4,096 tokens, 16,385 in the 16K variant | 8,192 tokens, 32,768 variant, 128,000 in GPT-4 Turbo |
| Coding | Competent on common patterns, weaker on debugging | Better at reading existing code and explaining failures |
| Factual accuracy | More prone to confident errors | Roughly 40% higher on OpenAI’s internal factuality evaluations |
| Following instructions | Drifted on long or layered prompts | Held complex instructions across longer outputs |
| Cost | Cheaper per token | Substantially more expensive per token |
| Availability in 2026 | Retired | Retired from ChatGPT, API versions winding down |
What Is ChatGPT-4?
ChatGPT-4 is not a product name OpenAI ever used. People use it to mean ChatGPT running on the GPT-4 model, which is a different thing from GPT-4 itself.
ChatGPT is the application: the chat interface, the conversation history, the file uploads, the web browsing. GPT-4 was one of the models that powered it.
The same confusion surrounds the difference between ChatGPT and GPT-3. ChatGPT launched in November 2022 on a model from the GPT-3.5 family, which is why “ChatGPT-3” stuck as a name for the free app even though no model was ever called that. GPT-4 arrived in the app four months later, for paying subscribers first.
The same interface has since run on GPT-4o, GPT-4.1, GPT-5, and now the GPT-5.6 series. ChatGPT stayed; the models underneath changed.
What Is GPT-4 and How Does It Work?
GPT-4 is a large multimodal model released by OpenAI on March 14, 2023. It accepts text and image inputs and produces text outputs.
Source: OpenAI, GPT-4 Technical Report.
Like its predecessors, it is a transformer-based model trained to predict the next token in a sequence. Training ran in two broad stages. First, the model was pre-trained on a large corpus of public and licensed data to predict the next token. Then it was fine-tuned with reinforcement learning from human feedback, which is what aligned its answers with what people actually wanted.
OpenAI did not publish the parameter count, the training data composition or the hardware details. The GPT-4 technical report explains that decision in terms of competitive and safety considerations, which was a departure from earlier releases.
The original knowledge cutoff was September 2021. GPT-4 Turbo, released in November 2023, moved that to April 2023 and expanded the context window to 128,000 tokens.
ChatGPT-3.5 vs ChatGPT-4: What Users Actually Noticed
If you are wondering how much better GPT 4 is on paper, the benchmark gap was massive. Anyone comparing ChatGPT 3 vs ChatGPT 4 day to day noticed four things instead.
Longer answers stayed coherent. GPT-3.5 tended to lose the thread in extended outputs, repeating itself or drifting from the original instruction. GPT-4 held structure across much longer responses.
Layered instructions worked. A prompt with four constraints would typically see GPT-3.5 satisfy two. GPT-4 handled all four more often, which is why it became the default for anything with a format requirement.
Fewer confident errors. Both models made things up. GPT-4 did it less, scoring 40% higher than the latest GPT-3.5 on OpenAI’s adversarial factuality evaluations. The technical report puts that at a 19-percentage-point gain. It was also more willing to say it did not know.
Images became usable input. Sending a screenshot, a chart, or a photo of handwritten notes and getting a useful answer was new.
GPT-3.5 vs GPT-4: Key Differences in Detail
The difference between ChatGPT 3 and 4 comes down to four measurable things. Reasoning, context, multimodality, and code. The GPT 3 vs GPT 4 gap is widest on the first.
Reasoning and Exam Performance
The clearest published gap was on standardized tests. OpenAI reported GPT-4 passing a simulated Uniform Bar Examination around the top 10% of test takers. GPT-3.5 scored around the bottom 10%.
That bar exam figure has since been challenged. A 2024 paper in Artificial Intelligence and Law found the comparison was skewed toward repeat test takers who had already failed the exam. Against all test takers, GPT-4’s score fell below the 69th percentile, and around the 48th on the essay section.
The pattern repeated across other exams: GPT-4 moved from passing to competitive on tests designed for humans. On MMLU, a benchmark spanning 57 subjects, GPT-4 reached 86.4% against 70.0% for GPT-3.5. It also hit a 67.0% pass rate on HumanEval, which measures Python function synthesis.
Benchmarks flatter models. The practical version of that gap was GPT-4 being usable for work where a wrong answer costs something.
Context Window
GPT-3.5 Turbo started at 4,096 tokens, roughly 3,000 words of combined input and output. The 16K variant raised that to 16,385, with output still capped at 4,096.
GPT-4 launched with 8,192 tokens and a 32,768 variant for longer documents. GPT-4 Turbo took it to 128,000 tokens, enough for a short book in a single conversation.
That difference decided which tasks were possible at all. Analyzing a 40-page contract was out of reach for GPT-3.5 and routine for GPT-4 Turbo.
Multimodality
GPT-3.5 accepted text and returned text. GPT-4 accepted images alongside text, which opened a category of tasks that had not existed in the product before.
Reading a diagram, extracting figures from a screenshot of a spreadsheet, describing what is wrong with a user interface. All of it required a model that could see.
Coding
Both models wrote code. The difference showed up in debugging.
GPT-3.5 was reasonable at producing a function from a description. GPT-4 was better at reading someone else’s code, tracing why it failed, and explaining the fix rather than rewriting the file.
ChatGPT-4 Features and Capabilities
The feature set that made GPT-4 a step change rather than an increment.
Image input. Charts, screenshots, photographs, handwritten notes and diagrams could all be sent as part of a prompt. Note the timing: image input was announced on March 14, 2023, but only Be My Eyes had access at first. It reached ChatGPT in late September 2023 as GPT-4V and the API in November 2023.
Longer context. Up to 128,000 tokens in GPT-4 Turbo, which covers long documents, extended conversations, and large code files.
More reliable adherence to system prompts. System messages already existed with gpt-3.5-turbo. What changed with GPT-4 is that the model actually followed them. A persona and a set of rules held across a conversation instead of drifting after a few turns.
Stronger instruction following. Multi-part requests with formatting rules, tone constraints and content requirements were handled more reliably.
Function calling. GPT-4 could return structured output matching a schema. That is what made it usable inside software rather than only as a chat interface.
What ChatGPT Added Around the Model
The app gained capabilities the model alone never had, and most of them shipped during the GPT-4 era.
Code Interpreter, later renamed Advanced Data Analysis, ran Python in a sandbox on uploaded files. Plugins connected ChatGPT to third-party services. Browsing let it read live web pages. Voice conversation arrived in September 2023, DALL·E 3 image generation in October 2023, and custom GPTs in November 2023.
That is the practical difference between the app and the model. GPT-4 could read an image. ChatGPT could read it, run code against the numbers in it, and draw a chart back.
Eight categories where GPT-4 was genuinely used in production, with what each looked like in practice.
Content Creation
Drafting, editing, and restructuring written material. A B2B SaaS team could feed GPT-4 a ten-page product whitepaper and ask for a five-email drip campaign and a LinkedIn carousel draft. Stripe used it on its own documentation, turning developer docs into summaries and answers.
The realistic role was first draft and structure. Anything with facts in it still needed checking, which is the same limitation that applies to current models.
Coding and Debugging
Writing functions, explaining unfamiliar code, and finding the reason a test fails. A developer pasting a stack trace and the relevant file would get a diagnosis and a patch more often than not. GitHub built Copilot X on GPT-4, adding chat and pull-request support to what had been autocomplete.
The 128,000 token window in GPT-4 Turbo mattered here. Whole modules could be read at once instead of in fragments.
Data and Document Analysis
Summarizing long documents, extracting structured data from unstructured text, and answering questions about a specific file. Legal and finance teams used it to pull key terms out of contracts and flag clauses that deviated from a template. Morgan Stanley deployed it across its wealth management research library, giving advisors a way to search content that had previously required knowing which document to open.
Accuracy depended on the document. Clean text worked well, scanned PDFs less so.
Image Understanding
Describing charts, reading screenshots, and interpreting diagrams. A data analyst could upload a messy Google Analytics chart and ask the model to summarize month-over-month traffic drops, without exporting the underlying data. Be My Eyes built a Virtual Volunteer on it for blind and low-vision users, which was the first production deployment of GPT-4 vision.
This was the capability GPT-3.5 could not do at all.
Customer Support
Drafting replies, classifying tickets and summarizing conversation history for a human agent. Support teams used it to write the first version of a response, with a person approving before sending. Intercom rebuilt its bot as Fin on GPT-4, answering from a company’s own help center rather than from scripted flows.
Full automation remained rare. The failure mode of a confidently wrong support answer is expensive.
Education
Explaining concepts at different levels, generating practice problems and grading free-text answers with feedback. Duolingo launched Duolingo Max with roleplay and explain-my-answer features, and Khan Academy built Khanmigo as a tutor that asks questions instead of giving answers.
Research
Literature summarization, hypothesis framing and drafting methods sections. Researchers used it to get oriented in an unfamiliar field quickly, then verified every citation, because invented references were a known failure.
Business Automation
Function calling made GPT-4 a component rather than a chat window. Classifying inbound email, extracting fields from forms and routing requests were the common patterns. Each had a schema the model had to match.
ChatGPT-4 Limitations
The same model that passed exams also failed in predictable ways.
Hallucination. It produced confident, plausible, wrong answers. Less often than GPT-3.5, and often enough that anything factual needed verification.
Knowledge cutoff. The original model knew nothing after September 2021. GPT-4 Turbo moved that to April 2023. Neither knew anything about events after their cutoff without a browsing tool.
Reasoning failures on novel problems. Performance on benchmarks did not always transfer to problems unlike anything in training.
Cost and speed. GPT-4 was significantly more expensive and slower than GPT-3.5. When analyzing chat GPT 4 vs 3.5 economics, many enterprise products used both, routing simple requests to the cheaper model.
No memory between sessions. Each conversation started from nothing unless the application supplied history.
Usage caps. ChatGPT Plus limited GPT-4 to 25 messages every three hours at launch, later raised to 40. Heavy users hit the ceiling daily.
Bias in outputs. The model reproduced patterns from its training data, including ones nobody wanted.
Prompt injection. Instructions hidden in a document or web page could override the developer’s own system prompt, which is still an open problem.
ChatGPT-4 Pricing: What It Cost
Pricing moved several times, and the figures below describe the period when GPT-4 was current rather than today.
ChatGPT Plus cost $20 a month and was the only way to reach GPT-4 in the consumer app when it launched. The free tier stayed on GPT-3.5 for over a year.
API pricing separated input and output tokens. GPT-4 with 8K context launched at $0.03 per 1,000 input tokens and $0.06 per 1,000 output tokens, and the 32K version at $0.06 and $0.12. GPT-3.5 Turbo sat at $0.0015 and $0.002 over the same period, which put GPT-4 roughly 15 to 30 times higher.
GPT-4 Turbo cut that sharply in November 2023, to $0.01 input and $0.03 output. Input became three times cheaper than GPT-4 and output half the price.
Current OpenAI pricing is published per model on the OpenAI platform pricing page. The GPT-5 family is priced well below original GPT-4 rates.
GPT-3 vs GPT-3.5 vs GPT-4: Understanding the Names
GPT-4 Turbo arrived in November 2023 as the same model family with three practical changes.
| GPT-4 | GPT-4 Turbo | |
|---|---|---|
| Released | 14 March 2023 | November 2023 |
| Context window | 8,192 tokens, 32,768 variant | 128,000 tokens |
| Knowledge cutoff | September 2021 | April 2023 |
| Input per 1,000 tokens | $0.03 | $0.01 |
| Output per 1,000 tokens | $0.06 | $0.03 |
| Speed | Slower | Faster |
The context jump was the one that changed what people built. Sixteen times more room meant whole codebases, long contracts and extended conversations fit in a single call, and it came with a price cut rather than a premium.
Most work described as GPT-4 after late 2023 was actually running on Turbo. The distinction rarely made it into product copy.
Is ChatGPT-4 Still Available in 2026?
No. GPT-4 and its successors have been removed from ChatGPT in stages, and the API versions are winding down.
The retirement timeline:
| Date | What happened | Source |
|---|---|---|
| 13 February 2026 | GPT-4o, GPT-4.1, GPT-4.1 mini and o4-mini retired from ChatGPT | OpenAI announcement |
| 17 February 2026 | chatgpt-4o-latest removed from the API | OpenAI deprecations page |
| 11 March 2026 | GPT-5.1 models retired from ChatGPT | OpenAI Help Center |
| 3 April 2026 | GPT-4o fully retired across all ChatGPT plans, including Custom GPTs | OpenAI Help Center |
| 27 June 2026 | GPT-4.5 retired from ChatGPT | OpenAI model release notes |
| 26 August 2026 | OpenAI o3 retired from ChatGPT | OpenAI model release notes |
Azure OpenAI runs its own retirement schedule for the GPT-4 series, with dates published on Microsoft’s model retirements page. Anyone running production traffic there should check it directly rather than relying on the ChatGPT timeline.
OpenAI’s own guidance is to migrate workloads to the GPT-5.6 family. Anything still calling a GPT-4 model ID should be audited against the OpenAI deprecations page.
One caveat worth knowing. Legacy deployment is stickier than the retirement schedule suggests. Orca Security’s analysis of 426 organizations found GPT-4o still the most common model in production AI systems. It was present in 37.6% of AI-adopting cloud environments.
GPT-4 vs Newer ChatGPT Models
GPT-4 sits four generations back in OpenAI’s lineup as of late 2026.
The sequence after chat 4: GPT-4 Turbo in November 2023, GPT-4o in May 2024, the o1 reasoning models in September 2024. Then GPT-4.1 in April 2025 and GPT-5 on August 7, 2025. Point releases from GPT-5.1 through GPT-5.5 followed across late 2025 and the first half of 2026, and OpenAI began previewing the GPT-5.6 series on June 27, 2026.
Source: OpenAI model release notes and deprecations page.
What changed most. Reasoning became a separate capability rather than a side effect of scale. Context windows grew by another order of magnitude, cost per token fell, and multimodality expanded beyond image input.
We cover the generational jump in a separate GPT-4 vs GPT-5 comparison, so this guide stays on GPT-4 and its immediate predecessor.
Is GPT-4 Still Worth Using?
For most new projects in 2026, newer models are generally the more practical choice. They offer improved capabilities and updated pricing, and OpenAI’s own guidance is to migrate.
There are two narrow exceptions. A system already built and validated on a GPT-4 model ID may not be worth rewriting before the retirement date forces it. And research reproducing published GPT-4 results needs the original model while it remains callable.
Both are temporary. Pinned model strings should be audited against both the OpenAI deprecations page and Microsoft’s Azure retirement schedule.
FAQs
What Is ChatGPT-4?
ChatGPT-4 is the informal name for ChatGPT running on the GPT-4 model. ChatGPT is the application and GPT-4 was the model powering it between March 2023 and its replacement by newer models.
When Did GPT-4 Come Out?
GPT-4 was released on March 14, 2023. API access became generally available to paying customers in July 2023, and GPT-4 Turbo followed in November 2023.
Is ChatGPT-4 Free?
Not in ChatGPT. GPT-4 required a Plus subscription at $20 a month when it launched, while the free tier ran on GPT-3.5. Free access did exist elsewhere, since Microsoft’s Bing Chat ran GPT-4 at no cost from early 2023, and GPT-4o reached the ChatGPT free tier in May 2024. The question is now historical, because GPT-4 is no longer selectable in ChatGPT at any tier.
Is GPT-4 Still Available?
Not in ChatGPT. The GPT-4 family was retired from the consumer app across 2026, with GPT-4o fully removed on April 3, 2026. The API versions carry their own retirement schedules on the OpenAI and Azure deprecation pages.
What Is the Difference Between GPT-3.5 and GPT-4?
On chat GPT 3 vs chatgpt 4, the most noticeable change was reasoning. GPT-4 handled multi-step logic, long documents and layered instructions substantially better, and it accepted images as input where GPT-3.5 was text only. Context windows differed by a factor of eight at launch and more than thirty in GPT-4 Turbo. GPT-4 also cost significantly more per token.
Is GPT-4 Better Than GPT-3.5?
When comparing GPT 4 vs GPT 3 on published benchmarks, GPT-4 wins across the board. The gap was largest on tasks needing multi-step reasoning. GPT-4 scored in the top 10% on a simulated bar exam, against the bottom 10% for GPT-3.5.
What Can GPT-4 Do?
GPT-4 handled text generation, coding and debugging, document analysis, image understanding, translation and structured data extraction. Function calling let it return output matching a schema, which made it usable inside software rather than only as a chat interface.
Can GPT-4 Analyze Images?
Yes. GPT-4 accepted image inputs alongside text and could describe charts, read screenshots, interpret diagrams and transcribe handwriting. It produced text output only, so it could read images but not generate them.
What Are GPT-4’s Limitations?
Hallucination, a fixed knowledge cutoff, inconsistent reasoning on genuinely novel problems, and cost and latency well above GPT-3.5. It also had no memory between sessions unless the application supplied conversation history.
Is GPT-4 Outdated in 2026?
Yes. It sits four generations back, is unavailable in ChatGPT, and the remaining API versions are scheduled for retirement. OpenAI recommends migrating to the GPT-5.6 family.
What Is the Difference Between Chat GPT 3 and 4 in Terms of Free Access?
Originally, GPT-3.5 powered the free tier while GPT-4 required a Plus subscription. Bing Chat offered free GPT-4 access separately, and GPT-4o reached the ChatGPT free tier in May 2024. Today both are retired, and free users get the GPT-5 series.
What Replaced GPT-4?
The difference between GPT-3 and GPT-4 was a generational jump, and so was everything after it. GPT-4 Turbo came first, then GPT-4o in 2024, then GPT-5 in August 2025. As of late 2026, the current lineup is the GPT-5 family, with the GPT-5.6 series in preview since June 27, 2026.
Conclusion: GPT-4’s Place in AI History
GPT-4 was the jump that changed what people expected from an AI assistant. The move from GPT-3.5 was not incremental, and the benchmark gaps understated how different the two felt to use.
It introduced multimodal workflows to a mainstream product. Sending a screenshot and getting a useful answer was new, and every model since has been expected to do it.
Function calling turned the model into a software component rather than a chat window. That single feature is why GPT-4 ended up inside products rather than only in browser tabs.
By 2026, it has been fully replaced, retired from ChatGPT and scheduled out of the API. OpenAI positions the GPT-5 family as the replacement for the work GPT-4 was used for.
The historical significance holds anyway. GPT-4 is the model that made the current generation of AI products look obvious in hindsight.
We build on these models for clients. One recent example is a GPT-based customer support chatbot that handles first-line queries against a company’s own documentation rather than generic training data.
Need help navigating the 2026 AI landscape, or migrating legacy GPT-4 applications onto the current lineup? Contact LITSLINK to talk through your stack.
