GPT-4.1 is OpenAI's premier large language model and represents a major advancement in artificial intelligence capabilities, performance, and adaptability. Building upon the foundation laid by earlier models such as GPT-4 and GPT-4o, GPT-4.1 demonstrates remarkable proficiency in both natural language understanding and code generation. It is engineered to deliver top-tier results across a wide variety of domains, from complex software engineering tasks to nuanced creative writing and deep analytical reasoning. One of its defining features is its extended context window—over 1 million tokens—which allows it to maintain coherence and accuracy over extremely long documents and intricate, multi-turn interactions. This capability is especially valuable for enterprises, developers, and researchers dealing with large-scale data or content-heavy workflows. Additionally, GPT-4.1 has been fine-tuned for instruction compliance, contextual awareness, and nuanced response generation, significantly improving its usefulness in real-world applications. With knowledge updated through June 2024, it serves as a reliable, state-of-the-art tool for a wide range of intelligent solutions. Whether it's building autonomous agents, drafting detailed reports, or supporting advanced chat systems, GPT-4.1 sets a new standard in AI versatility and performance, offering a powerful blend of depth, speed, and cost-efficiency for professional use.

GPT-4.1

GPT-4.1 Mini is a streamlined, high-efficiency version of OpenAI’s flagship GPT-4.1 model, designed for environments where performance, speed, and cost-effectiveness are essential. While more compact than its full-sized counterpart, GPT-4.1 Mini delivers impressive capabilities, rivaling or even surpassing earlier advanced models like GPT-4o in many real-world scenarios. It excels in applications that require fast, responsive AI systems such as customer support chatbots, productivity tools, and dynamic virtual assistants. A standout feature of GPT-4.1 Mini is that, despite its reduced computational footprint, it retains the same 1 million token context window as the full GPT-4.1, enabling it to manage lengthy conversations or documents with surprising accuracy and coherence. The model maintains strong instruction-following behavior, advanced reasoning capabilities, and a deep understanding of language, allowing developers to deploy intelligent, high-functioning AI at scale without excessive infrastructure requirements. Ideal for businesses seeking a high-performing model with lower latency and operational costs, GPT-4.1 Mini strikes a well-calibrated balance between power and efficiency, empowering teams to build agile, scalable AI applications that don’t compromise on intelligence or quality.

GPT-4.1 Mini

GPT-4.1 Nano is the most lightweight and cost-efficient model in the GPT-4.1 lineup, optimized for scenarios that demand extremely fast response times and minimal resource consumption. Designed with scalability in mind, it is ideal for high-volume, real-time applications such as autocomplete engines, spam detection, sentiment analysis, instant data tagging, and embedded AI in mobile or edge devices. What sets GPT-4.1 Nano apart from other lightweight models is its ability to maintain strong contextual awareness and accurate language understanding, even within a much smaller compute footprint. Remarkably, it still benefits from the same extended 1 million token context window as the larger GPT-4.1 models, allowing it to process long-form inputs and extended conversations with consistency and coherence. This makes it a powerful yet affordable choice for enterprises looking to integrate intelligent AI into distributed systems or latency-sensitive environments. Despite its smaller size, GPT-4.1 Nano offers a level of performance and responsiveness that enables developers to create AI-driven experiences that feel smooth, smart, and immediate—without the infrastructure overhead typically associated with more complex models.

GPT-4.1 Nano

GPT-4.5 Preview is OpenAI’s next-generation general-purpose language model, launched in early 2025 as a significant evolution in conversational AI. Positioned as the most advanced model in the GPT lineup at the time of its release, GPT-4.5 introduces enhancements that prioritize fluid, natural-sounding interactions, aiming to make conversations with AI feel more intuitive, emotionally resonant, and human-like. The model benefits from extended pretraining and advanced fine-tuning techniques, including reinforcement learning from human feedback (RLHF), which help reduce hallucinations, improve factual reliability, and sharpen instruction-following abilities. Unlike earlier versions more focused on logic or code, GPT-4.5 emphasizes expressive communication, creativity, and contextual nuance—making it particularly effective for applications like interactive storytelling, empathetic virtual assistants, and emotionally aware customer service agents. Though OpenAI has not disclosed the model’s parameter count, GPT-4.5 is considered the most capable language model in its class, equipped to handle a broad range of complex tasks with reduced error rates and enhanced linguistic fluency. Whether generating compelling narratives or assisting in emotionally intelligent dialogues, GPT-4.5 represents a significant step forward in making AI feel not just smarter, but also more personable and relatable.

GPT-4.5 Preview

GPT-4o is OpenAI’s powerful multimodal model that seamlessly integrates both text and visual inputs, offering users a robust, low-latency AI experience ideal for dynamic, real-time use cases. With a substantial context window of 128,000 tokens, GPT-4o can process and respond to long documents, deep conversations, and complex multimodal tasks with impressive efficiency. It expands on the capabilities of GPT-4 by not only maintaining high-quality language generation but also enhancing image understanding—allowing for more intelligent interaction across multiple input formats. Designed for speed and computational efficiency, GPT-4o delivers faster response times while consuming fewer resources, making it well-suited for practical applications like interactive virtual agents, live support bots, and creative tools that blend image and text generation. Despite its performance-focused architecture, GPT-4o does not compromise on depth or accuracy. It is highly effective in areas like visual question answering, document summarization, and interactive education, and it stands out as a balanced choice for developers and organizations looking to deploy multimodal AI at scale. Its combination of responsiveness, capability, and accessibility cements its role as a cornerstone of OpenAI’s model ecosystem.

GPT-4o

GPT-4o Mini is a highly optimized, lightweight version of OpenAI’s GPT-4o, engineered for high-efficiency deployment in environments where resources are limited but intelligent functionality is still essential. Built through a process of model distillation, GPT-4o Mini retains the key strengths of its larger counterpart—such as high-quality language generation and solid contextual awareness—while significantly reducing computational demands. This makes it ideal for use cases in mobile apps, edge devices, and low-latency systems that require reliable AI interaction without the overhead of large infrastructure. GPT-4o Mini maintains support for multimodal tasks, meaning it can still handle both text and visual inputs with competence, despite its smaller size. Its reduced latency and fast response times make it a strong choice for real-time digital agents, educational applications, or lightweight productivity tools. Developers and businesses benefit from its scalability and cost-effectiveness, enabling broader AI adoption across platforms and industries. By striking a careful balance between speed, intelligence, and accessibility, GPT-4o Mini serves as a versatile solution for teams seeking compact, powerful AI systems that deliver strong performance without the expense or complexity of larger models.

GPT-4o Mini

GPT-4 is OpenAI’s groundbreaking large multimodal model, representing a major leap in language understanding, reasoning, and generative capabilities. Designed to handle both text and image inputs, GPT-4 brings an unprecedented level of versatility and performance to a wide range of applications, including content generation, advanced problem-solving, creative writing, tutoring, and more. It leverages a highly advanced transformer architecture and has been trained on a vast, diverse dataset to improve accuracy, relevance, and contextual understanding. While OpenAI has not disclosed the exact parameter count, GPT-4 is believed to be among the largest and most powerful language models developed, rumored to surpass one trillion parameters. This scale allows it to excel on professional and academic benchmarks, demonstrating human-level competence in standardized testing and technical tasks. With improved alignment and safety features, GPT-4 offers more reliable outputs and better adherence to user instructions compared to its predecessors. Its multimodal nature allows users to interact with it using both images and text, opening up powerful use cases in areas like visual analysis, document processing, and multimodal creativity. GPT-4 sets the foundation for OpenAI’s next generation of AI-driven experiences.

GPT-4

GPT-3.5 Turbo is an enhanced version of OpenAI’s GPT-3.5 model, specifically engineered to provide a high-performance, cost-efficient solution for a wide variety of natural language processing tasks. Featuring a 16,385-token context window, GPT-3.5 Turbo can handle moderately long inputs, making it well-suited for multi-turn conversations, structured prompts, and document-based workflows. Known for its responsiveness and balance between power and efficiency, it has become one of the most widely adopted models for developers and businesses seeking reliable AI functionality without the cost or complexity of larger flagship models like GPT-4. Its optimized architecture enables fast inference and reduced latency, making it an ideal candidate for real-time applications such as chatbots, virtual assistants, automated content creation, and customer service interfaces. GPT-3.5 Turbo also maintains strong instruction-following capabilities and natural language understanding, allowing it to perform effectively in both casual interactions and more structured information tasks. Its popularity stems from its ability to scale across diverse use cases while maintaining a reasonable resource footprint, offering an excellent starting point for organizations and individuals entering the world of AI-powered applications.

GPT 3.5 Turbo

The o1 model is a specialized large language model built with a clear emphasis on advanced reasoning, deep comprehension, and long-context processing. With an impressive 200,000-token context window, o1 is designed to retain and analyze vast amounts of information over extended interactions, making it a powerful tool for tasks that demand detailed logical reasoning and consistency. It excels in domains where critical thinking and information retention are essential, such as legal analysis, technical documentation, academic research, and enterprise-grade knowledge work. Unlike general-purpose conversational models, o1 is engineered to prioritize structured reasoning and context-aware outputs, reducing noise and improving factual alignment in complex problem-solving scenarios. Its architecture is tailored to support lengthy documents, intricate workflows, and deep exploration of topics, giving it a competitive edge in professional and analytical environments. Whether used for long-form content generation, legal drafting, or scientific synthesis, o1 delivers clarity, structure, and precision. It stands out as a high-performance alternative to conventional models, giving organizations the tools to manage intensive reasoning tasks without sacrificing accuracy or depth.

o3-mini is a compact yet powerful variant of the o3 model series, designed to deliver robust reasoning capabilities and long-context processing in a more accessible, resource-efficient format. Equipped with a 200,000-token context window, it can analyze and retain large volumes of data, supporting tasks such as document summarization, technical analysis, and multi-step logical workflows. Despite its smaller footprint compared to full-scale models, o3-mini is highly capable in scenarios that require both reasoning depth and quick response times, making it well-suited for real-time AI systems like analytics dashboards, intelligent support bots, and knowledge assistants. Its architecture is optimized for performance without compromising on the ability to understand complex inputs, follow structured instructions, and deliver consistent, contextually relevant outputs. By balancing processing power and operational cost, o3-mini enables organizations to scale their AI deployments across diverse platforms, from cloud systems to embedded applications. It’s a go-to choice for teams seeking advanced AI performance that can operate within tighter budgets and faster compute environments, making it ideal for practical use in fast-moving enterprise settings.

o3-mini

o1-mini is a streamlined version of the o1 model, designed to maintain high-level reasoning and comprehension abilities while operating within a lighter, more resource-efficient framework. With a 128,000-token context window, it supports extensive input processing and is well-suited for tasks that require detailed understanding and multi-step reasoning, even in environments with limited computational resources. o1-mini is ideal for use cases like intelligent digital agents, document classification, automated insights extraction, and data labeling workflows where both speed and comprehension are critical. It offers businesses and developers a more affordable alternative to larger models, without significantly sacrificing the sophistication needed for enterprise-grade applications. Thanks to its intelligent compression of model architecture, o1-mini can handle nuanced instructions, maintain coherent long-form responses, and draw insights from complex datasets, making it particularly effective for knowledge work at scale. Whether deployed in customer-facing tools, internal research systems, or edge computing environments, o1-mini brings the analytical capabilities of larger models into a compact, deployable form tailored for high-efficiency operations.

Model	Input Cost	Output Cost	Total	Est. Monthly
GPT-4.1 Nano	$0.1000	$0.4000	$0.5000	$0.18
GPT-4o Mini	$0.1500	$0.6000	$0.7500	$0.26
GPT-4.1 Mini	$0.4000	$1.6000	$2.0000	$0.70
GPT 3.5 Turbo	$0.5000	$1.5000	$2.0000	$0.75
o3-mini	$1.1000	$4.4000	$5.5000	$1.93
o1-mini	$1.1000	$4.4000	$5.5000	$1.93
GPT-4.1	$2.0000	$8.0000	$10.0000	$3.50
GPT-4o	$2.5000	$10.0000	$12.5000	$4.38
o1	$15.0000	$60.0000	$75.0000	$26.25
GPT-4	$30.0000	$60.0000	$90.0000	$37.50
GPT-4.5 Preview	$75.0000	$75.0000	$150.0000	$75.00

OpenAI

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Average Price per Million Tokens

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