# OpenAI GPT-4 Turbo Launch GPT-4 Turbo is a large language model released by OpenAI in November 2023, featuring a 128K context window and reduced pricing compared to GPT-4. It was announced alongside a vision-capable variant and succeeded by GPT-4o in 2024. GPT-4 Turbo is a large language model developed by [OpenAI](https://www.wikiprompt.org/wiki/openai), announced in November 2023 as an enhanced version of the earlier GPT-4 model. Its most notable improvements include a 128K token context window, allowing the model to process significantly longer inputs, and a lower API pricing structure. The release also introduced GPT-4 Turbo with Vision, a variant capable of processing both text and images. GPT-4 Turbo was succeeded by GPT-4o in May 2024, which offered real-time multimodal processing and free access to ChatGPT users. ## Background OpenAI introduced the first GPT model in 2018, based on the [transformer](https://www.wikiprompt.org/wiki/transformer) architecture and trained on a large corpus of books. Subsequent iterations, GPT-2 in 2019 and GPT-3 in 2020, scaled up parameters and improved text generation. GPT-3.5 powered the initial release of ChatGPT in November 2022, which brought large language models to mainstream attention. GPT-4, released in March 2023, added multimodal capabilities, accepting both text and image inputs. The default version had an 8K context window, with a special API variant supporting up to 32K tokens. GPT-4 Turbo was developed to address limitations in context length and cost, building on the foundation of its predecessor. ## Announcement and Release OpenAI announced GPT-4 Turbo on November 6, 2023, at its first developer conference, DevDay, held in San Francisco. The model was made available through the OpenAI API, with pricing set at $0.01 per 1,000 input tokens and $0.03 per 1,000 output tokens, roughly three times cheaper than GPT-4. The 128K context window enabled processing of documents exceeding 300 pages of text in a single request. OpenAI also introduced an updated version of GPT-4 Turbo with Vision, which could analyze images alongside text. The announcement highlighted improvements in instruction following, JSON mode, and function calling, making the model more suitable for developer applications. ## Capabilities GPT-4 Turbo retained the multimodal input capabilities of GPT-4, allowing users to provide both text and images. It could interact with external tools through function calling, enabling tasks such as web searches, API calls, and image generation. The expanded context window allowed the model to maintain coherence over longer conversations and process entire books or codebases. In a 2023 article in Nature, programmers reported that GPT-4 Turbo assisted in coding tasks, such as identifying errors and suggesting optimizations, though it was prone to mistakes. On a test of 89 security scenarios, GPT-4 produced code vulnerable to SQL injection attacks 5% of the time, an improvement over GitHub Copilot from 2021, which had a 40% vulnerability rate. ### Standardized Test Performance Studies on GPT-4 Turbo's performance on standardized tests were limited, but earlier evaluations of GPT-4 showed strong results. In the Torrance Tests of Creative Thinking, GPT-4 scored within the top 1% for originality and fluency, with flexibility scores ranging from the 93rd to the 99th percentile. Researchers cautioned that running chatbots through such tests may not be reliable, as the models can generate plausible but incorrect answers. ### Medical Applications Microsoft researchers tested GPT-4 on medical problems and found that it exceeded the passing score on the United States Medical Licensing Examination by over 20 points, outperforming earlier models like GPT-3.5 and specialized models such as Med-PaLM. However, they warned of significant risks, including inaccurate recommendations and hallucinations of major factual errors. In April 2023, Microsoft and Epic Systems announced plans to provide healthcare providers with GPT-4-powered systems for answering patient questions and analyzing medical records, a trend that continued with GPT-4 Turbo. ## Limitations Like its predecessors, GPT-4 Turbo could hallucinate, producing outputs that contradict the user's prompt or contain fabricated information. It also lacked transparency in decision-making; when asked to explain its reasoning, the model generated post-hoc explanations that could not be verified as reflecting the actual process. In 2023, researchers tested GPT-4 against the ConceptARC benchmark, designed to measure abstract reasoning, and found it scored below 33% on all categories, while specialized models scored 60% on most and humans scored at least 91%. Sam Bowman, not involved in the research, noted that the visual nature of the test may disadvantage a language model. ### Bias GPT-4 Turbo was trained in two stages: first, on large internet text datasets to predict the next token, and second, using reinforcement learning from human feedback to align with safety guidelines. Microsoft researchers suggested that GPT-4 exhibited cognitive biases such as confirmation bias, anchoring, and base-rate neglect. The training process aimed to reduce harmful outputs, but biases could still emerge. ## Training OpenAI did not disclose technical details of GPT-4 Turbo's training, including model size, architecture, or hardware. The technical report for GPT-4, which likely applied to Turbo, cited competitive and safety concerns for this secrecy. Sam Altman stated that training GPT-4 cost more than $100 million. The training used supervised learning followed by reinforcement learning with both human and AI feedback, but specifics such as hyperparameters and dataset construction were not revealed. ## Reception and Impact GPT-4 Turbo was well received by developers due to its lower cost and larger context window, which enabled new applications such as long-document analysis and complex agent workflows. It reinforced OpenAI's position in the competitive landscape of [large language models](https://www.wikiprompt.org/wiki/large-language-model), facing rivals like [Anthropic](https://www.wikiprompt.org/wiki/anthropic) and [Google DeepMind](https://www.wikiprompt.org/wiki/google-deepmind). The release also highlighted the trend toward more efficient and accessible AI models, influencing subsequent developments in the field. GPT-4 Turbo remained available in the OpenAI API until it was eventually replaced by newer models, though GPT-4 itself was removed from ChatGPT in 2025. --- Source: https://www.wikiprompt.org/wiki/openai-gpt-4-turbo-launch License: CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/) Last updated: 2026-09-12T16:25:09.883421+00:00