The company has popularized
generative pretrained transformers (GPT).
OpenAI's original GPT model ("GPT-1") The original paper on generative pre-training of a
transformer-based language model was written by
Alec Radford and his colleagues, and published as a preprint on OpenAI's website on June 11, 2018. It showed how a
generative model of language could acquire world knowledge and process long-range dependencies by pre-training on a diverse corpus with long stretches of contiguous text.
GPT-2 Generative Pre-trained Transformer 2 ("GPT-2") is an
unsupervised transformer language model and the successor to OpenAI's original GPT model ("GPT-1"). GPT-2 was announced in February 2019, with only limited demonstrative versions initially released to the public. The full version of GPT-2 was not immediately released due to concerns about potential misuse, including applications for writing
fake news. Some experts expressed skepticism that GPT-2 posed a significant threat. In response to GPT-2, the Allen Institute for Artificial Intelligence responded with a tool to detect "neural fake news". Other researchers, such as Jeremy Howard, warned of "the technology to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be impossible to filter". In November 2019, OpenAI released the complete version of the GPT-2 language model. Several websites host interactive demonstrations of different instances of GPT-2 and other transformer models. GPT-2's authors argue that unsupervised language models are general-purpose learners, illustrated by GPT-2 achieving state-of-the-art accuracy and
perplexity on 7 of 8
zero-shot tasks (i.e., the model was not further trained on any task-specific input-output examples). The corpus it was trained on, called WebText, contains slightly 40 gigabytes of text from
URLs shared in
Reddit submissions with at least 3
upvotes. It avoids certain issues encoding vocabulary with word tokens by using
byte pair encoding. This permits representing any string of characters by encoding both individual characters and multiple-character tokens.
GPT-3 First described in May 2020, Generative Pre-trained Transformer 3 (GPT-3) is an unsupervised transformer language model and the successor to
GPT-2. OpenAI stated that GPT-3 succeeded at certain "
meta-learning" tasks and could generalize the purpose of a single input-output pair. The GPT-3 release paper gave examples of translation and cross-linguistic
transfer learning between English and Romanian, and between English and German. GPT-3 dramatically improved benchmark results over GPT-2. OpenAI cautioned that such scaling-up of language models could be approaching or encountering the fundamental capability limitations of predictive language models. Pre-training GPT-3 required several thousand petaflop/s-days of compute, compared to tens of petaflop/s-days for the full GPT-2 model. On September 23, 2020, GPT-3 was licensed exclusively to Microsoft.
Codex Announced in mid-2021, Codex is a descendant of GPT-3 that has additionally been trained on code from 54 million GitHub repositories, and is the AI powering the code
autocompletion tool
GitHub Copilot. According to OpenAI, the model can create working code in over a dozen programming languages, most effectively in Python. OpenAI announced that they would discontinue support for the Codex API on March 23, 2023.
GPT-4 On March 14, 2023, OpenAI announced the release of Generative Pre-trained Transformer 4 (GPT-4), capable of accepting text or image inputs. They announced that the updated technology passed a simulated law school bar exam with a score around the top 10% of test takers. (By contrast, GPT-3.5 scored around the bottom 10%.) They said that GPT-4 could also read, analyze or generate up to 25,000 words of text, and write code in all major programming languages. Observers reported that the iteration of ChatGPT using GPT-4 was an improvement on the previous GPT-3.5-based iteration, with the caveat that GPT-4 retained some of the problems with earlier revisions. GPT-4 is also capable of taking images as input on ChatGPT. OpenAI has declined to reveal various technical details and statistics about GPT-4, such as the precise size of the model.
GPT-4o On May 13, 2024, OpenAI announced and released
GPT-4o, which can process and generate text, images and audio. GPT-4o achieved state-of-the-art results in voice, multilingual, and vision benchmarks, setting new records in audio speech recognition and translation. It scored 88.7% on the Massive Multitask Language Understanding (
MMLU) benchmark compared to 86.5% by GPT-4. On July 18, 2024, OpenAI released GPT-4o mini, a smaller version of GPT-4o replacing GPT-3.5 Turbo on the ChatGPT interface. Its
API costs $0.15 per million input tokens and $0.60 per million output tokens, compared to $5 and $15, respectively, for GPT-4o. OpenAI expects it to be particularly useful for enterprises, startups and developers seeking to automate services with AI agents. In March 2025, OpenAI released GPT-4o's native image generation feature, as an alternative to DALL-E 3.
GPT-4.5 On February 27, 2025, OpenAI released
GPT-4.5, codenamed Orion. Sam Altman claimed that GPT-4.5 would present inaccurate information less frequently than previous models, and described it as a "giant, expensive model".
GPT-4.1 On April 14, 2025, OpenAI released the
GPT-4.1 model. They also released two “smaller, faster, and cheaper” models including GPT-4.1 mini and GPT-4.1 nano.
GPT-5 GPT-5 is
OpenAI’s flagship model released on August 7, 2025. It replaced earlier models like
GPT-4o,
GPT-4.5, and
o3. GPT-5 uses a dynamic router that chooses between quick responses and deeper “thinking” when needed. It can perform at PhD-level across domains like math, coding, health, and multimodal tasks. It also achieved a 74.9% on SWE-bench Verified and 88% on Aider polyglot. Reporters described the GPT-5 launch as a major milestone moving toward AGI, praising its intelligence, accessibility, and affordability. But some early feedback called it “evolutionary rather than revolutionary”, noting mixed results in creative writing and pointing to competition from models like
Grok 4 Heavy.
o1 On September 12, 2024, OpenAI released the o1-preview and o1-mini models, which have been designed to take more time to think about their responses, leading to higher accuracy. These models are particularly effective in science, coding, and reasoning tasks, and were made available to ChatGPT Plus and Team members. In December 2024, o1-preview was replaced by o1. In March 2025, the o1-Pro model was made available through OpenAI's developer API, which was previously available to ChatGPT Pro users since December 2024. The pricing is $150 per million input tokens and $600 per million output tokens.
o3 On December 20, 2024, OpenAI unveiled o3, the successor of the o1 reasoning model. OpenAI also unveiled o3-mini, a lighter and faster version of OpenAI o3. As of December 21, 2024, this model is not available for public use. According to OpenAI, they are testing o3 and o3-mini. Until January 10, 2025, safety and security researchers had the opportunity to apply for early access to these models. The model is called o3 rather than o2 to avoid confusion with telecommunications services provider
O2.
Deep research Deep research is an
AI agent developed by OpenAI, unveiled on February 2, 2025. It leverages the capabilities of OpenAI's o3 model to perform extensive web browsing, data analysis, and synthesis, delivering comprehensive reports within a timeframe of 5 to 30 minutes. With browsing and
Python tools enabled, it reached an accuracy of 26.6 percent on
HLE (Humanity's Last Exam) benchmark. In April 2025, OpenAI started rolling out a lightweight version of Deep Research to all its ChatGPT free users.
GPT-OSS GPT-OSS (stylized as gpt-oss) is a set of open-weight reasoning models released by OpenAI on August 5, 2025. They come in two variants: a larger 117-billion-parameter model called
gpt-oss-120b, and a smaller 21-billion-parameter model called
gpt-oss-20b. Both models are released under an
Apache 2.0 licence, allowing commercial and non-commercial use. In terms of performance, they are comparable to
o4-mini and
o3-mini respectively, according to OpenAI. gpt-oss-20b is small enough to run on a device with over 16
gigabytes of
random access memory. ==Image classification==