# OpenAI GPT-4 Release GPT-4 is a multimodal large language model released by OpenAI on March 14, 2023, capable of processing text and images. It improved on predecessors in reasoning, coding, and standardized tests, though OpenAI withheld technical details. GPT-4 is a large language model developed by [OpenAI](https://www.wikiprompt.org/wiki/openai), released on March 14, 2023, as the fourth in its GPT foundation model series. It is a multimodal model, accepting both text and images as input, and is noted for its strong performance on various benchmarks, including standardized tests and coding tasks. OpenAI has not disclosed technical details such as model size, architecture, or training hardware, citing competitive and safety concerns. GPT-4 is preceded by [GPT-3.5](https://www.wikiprompt.org/wiki/large-language-model) and followed by GPT-5; a version named GPT-4V handles image inputs, and the later GPT-4o model (May 2024) extends to real-time audio and video processing. GPT-4 was integrated into Microsoft's Bing Chat in February 2023, released in ChatGPT in March 2023, and removed from ChatGPT in 2025, though it remains available via OpenAI's API. ## Background and Development OpenAI introduced the first GPT model in 2018, based on the [transformer architecture](https://www.wikiprompt.org/wiki/transformer), trained on book corpora for language understanding. GPT-2 (2019) was a larger model capable of generating coherent text, and GPT-3 (2020) scaled parameters over 100 times compared to GPT-2. GPT-3.5 powered the ChatGPT chatbot launched in late 2022. GPT-4 was built on this lineage, incorporating improvements in multimodal learning, [reinforcement learning](https://www.wikiprompt.org/wiki/reinforcement-learning), and safety alignment. An early version was tested in Bing Chat from February 2023, giving Microsoft users early access before the public release. ## Capabilities and Features The default GPT-4 model had an 8K token context window, with a special API version supporting up to 32K tokens. Unlike predecessors, it could process images, enabling users to upload photos for analysis or questions. The model could be prompted to interact with external tools, such as web searches using tags, allowing it to fetch real-time information and perform tasks beyond text prediction, including API calls and image generation. In November 2023, OpenAI announced GPT-4 Turbo and GPT-4 Turbo with Vision, offering a 128K context window at lower cost. ## Performance on Standardized Tests GPT-4 demonstrated high aptitude on various exams. In the [Torrance Tests of Creative Thinking](https://www.wikiprompt.org/wiki/artificial-intelligence), it scored within the top 1% for originality and fluency, with flexibility scores ranging from the 93rd to 99th percentile. Researchers at Microsoft found GPT-4 exceeded the passing score on the USMLE by over 20 points, outperforming GPT-3.5 and specialized medical models like Med-PaLM, without any prompt engineering. However, the same study warned of significant risks in medical applications due to potential inaccuracies and hallucinations. ## Applications and Impact A 2023 Nature article highlighted GPT-4's usefulness in coding, such as debugging and optimization. One biophysicist reported porting a MATLAB program to Python took hours instead of days. In security testing, GPT-4 generated SQL-injection-vulnerable code 5% of the time, compared to GitHub Copilot's 40% in 2021. In healthcare, Microsoft and Epic Systems announced in April 2023 plans to use GPT-4 for patient query responses and medical record analysis, though caution was advised. ## Limitations and Risks GPT-4 is known to hallucinate, producing outputs not grounded in training data or contradicting user prompts. Its decision-making is opaque; explanations are generated post-hoc and may conflict with prior statements. In 2023, the ConceptARC benchmark showed GPT-4 scored below 33% on abstract reasoning tasks, while specialized models and humans scored higher, though skeptics noted the visual nature of the test may disadvantage a language model. ## Bias and Alignment GPT-4's training involved two stages: initial unsupervised learning on internet text, followed by [reinforcement learning from human feedback](https://www.wikiprompt.org/wiki/rlhf) to reduce harmful outputs. Microsoft researchers suggested it may exhibit cognitive biases like confirmation bias, anchoring, and base-rate neglect, raising concerns about fairness in deployment. ## Training and Technical Secrecy OpenAI's technical report for GPT-4 omitted model size, architecture, hardware, training dataset construction, computing power, and hyperparameters like learning rate or optimizers. The company cited "competitive landscape and safety implications" as reasons. CEO [Sam Altman](https://www.wikiprompt.org/wiki/sam-altman) stated training cost exceeded $100 million, with reports from Semafor indicating higher figures, though exact numbers remain unverified. ## Successors and Evolution GPT-4o, introduced on May 13, 2024, processes text, audio, and images in real time with human-like response times. It improved non-English language performance and was made available to free-tier users, unlike GPT-4. GPT-4V, launched earlier, specifically added image input to GPT-4. The model's legacy includes advancing multimodal AI and sparking debates on transparency and safety in large language models. --- Source: https://www.wikiprompt.org/wiki/openai-gpt-4-release License: CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/) Last updated: 2026-09-13T03:52:41.443595+00:00