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OpenAI o3-mini is a lightweight, efficient AI model from OpenAI’s "o3" series, designed to balance cost, speed, and intelligence. It is optimized for faster inference and lower computational costs, making it an ideal choice for businesses and developers who need AI-powered applications without the high expense of larger models like GPT-4o.


OpenAI o3-mini is a lightweight, efficient AI model from OpenAI’s "o3" series, designed to balance cost, speed, and intelligence. It is optimized for faster inference and lower computational costs, making it an ideal choice for businesses and developers who need AI-powered applications without the high expense of larger models like GPT-4o.


OpenAI o3-mini is a lightweight, efficient AI model from OpenAI’s "o3" series, designed to balance cost, speed, and intelligence. It is optimized for faster inference and lower computational costs, making it an ideal choice for businesses and developers who need AI-powered applications without the high expense of larger models like GPT-4o.

OpenAI’s Real-Time API is a game-changing advancement in AI interaction, enabling developers to build apps that respond instantly—literally in milliseconds—to user inputs. It drastically reduces the response latency of OpenAI’s GPT-4o model to as low as 100 milliseconds, unlocking a whole new world of AI-powered experiences that feel more human, responsive, and conversational in real time. Whether you're building a live voice assistant, a responsive chatbot, or interactive multiplayer tools powered by AI, this API puts real in real-time AI.


OpenAI’s Real-Time API is a game-changing advancement in AI interaction, enabling developers to build apps that respond instantly—literally in milliseconds—to user inputs. It drastically reduces the response latency of OpenAI’s GPT-4o model to as low as 100 milliseconds, unlocking a whole new world of AI-powered experiences that feel more human, responsive, and conversational in real time. Whether you're building a live voice assistant, a responsive chatbot, or interactive multiplayer tools powered by AI, this API puts real in real-time AI.


OpenAI’s Real-Time API is a game-changing advancement in AI interaction, enabling developers to build apps that respond instantly—literally in milliseconds—to user inputs. It drastically reduces the response latency of OpenAI’s GPT-4o model to as low as 100 milliseconds, unlocking a whole new world of AI-powered experiences that feel more human, responsive, and conversational in real time. Whether you're building a live voice assistant, a responsive chatbot, or interactive multiplayer tools powered by AI, this API puts real in real-time AI.


text-embedding-3-large is OpenAI’s most advanced embedding model designed to convert natural language text into high-dimensional vector representations. With 3,072 dimensions per embedding and cutting-edge architecture, it offers best-in-class performance for tasks like semantic search, content recommendations, clustering, classification, and more. Built to deliver top-tier semantic understanding, this model is ideal when accuracy and relevance are mission-critical. It’s the spiritual successor to text-embedding-ada-002, bringing huge improvements in contextual understanding, generalization, and relevance scoring.


text-embedding-3-large is OpenAI’s most advanced embedding model designed to convert natural language text into high-dimensional vector representations. With 3,072 dimensions per embedding and cutting-edge architecture, it offers best-in-class performance for tasks like semantic search, content recommendations, clustering, classification, and more. Built to deliver top-tier semantic understanding, this model is ideal when accuracy and relevance are mission-critical. It’s the spiritual successor to text-embedding-ada-002, bringing huge improvements in contextual understanding, generalization, and relevance scoring.


text-embedding-3-large is OpenAI’s most advanced embedding model designed to convert natural language text into high-dimensional vector representations. With 3,072 dimensions per embedding and cutting-edge architecture, it offers best-in-class performance for tasks like semantic search, content recommendations, clustering, classification, and more. Built to deliver top-tier semantic understanding, this model is ideal when accuracy and relevance are mission-critical. It’s the spiritual successor to text-embedding-ada-002, bringing huge improvements in contextual understanding, generalization, and relevance scoring.


o1-pro is a highly capable AI model developed by OpenAI, designed to deliver efficient, high-quality text generation across a wide range of use cases. As part of OpenAI’s GPT-4 architecture family, o1-pro is optimized for low-latency performance and high accuracy—making it suitable for both everyday tasks and enterprise-scale applications. It powers natural language interactions, content creation, summarization, and more, offering developers a solid balance between performance, cost, and output quality.


o1-pro is a highly capable AI model developed by OpenAI, designed to deliver efficient, high-quality text generation across a wide range of use cases. As part of OpenAI’s GPT-4 architecture family, o1-pro is optimized for low-latency performance and high accuracy—making it suitable for both everyday tasks and enterprise-scale applications. It powers natural language interactions, content creation, summarization, and more, offering developers a solid balance between performance, cost, and output quality.


o1-pro is a highly capable AI model developed by OpenAI, designed to deliver efficient, high-quality text generation across a wide range of use cases. As part of OpenAI’s GPT-4 architecture family, o1-pro is optimized for low-latency performance and high accuracy—making it suitable for both everyday tasks and enterprise-scale applications. It powers natural language interactions, content creation, summarization, and more, offering developers a solid balance between performance, cost, and output quality.


GPT-4.1 is OpenAI’s newest multimodal large language model, designed to deliver highly capable, efficient, and intelligent performance across a broad range of tasks. It builds on the foundation of GPT-4 and GPT-4 Turbo, offering enhanced reasoning, greater factual accuracy, and smoother integration with tools like code interpreters, retrieval systems, and image understanding. With native support for a 128K token context window, function calling, and robust tool usage, GPT-4.1 brings AI closer to behaving like a reliable, adaptive assistant—ready to work, build, and collaborate across tasks with speed and precision.


GPT-4.1 is OpenAI’s newest multimodal large language model, designed to deliver highly capable, efficient, and intelligent performance across a broad range of tasks. It builds on the foundation of GPT-4 and GPT-4 Turbo, offering enhanced reasoning, greater factual accuracy, and smoother integration with tools like code interpreters, retrieval systems, and image understanding. With native support for a 128K token context window, function calling, and robust tool usage, GPT-4.1 brings AI closer to behaving like a reliable, adaptive assistant—ready to work, build, and collaborate across tasks with speed and precision.


GPT-4.1 is OpenAI’s newest multimodal large language model, designed to deliver highly capable, efficient, and intelligent performance across a broad range of tasks. It builds on the foundation of GPT-4 and GPT-4 Turbo, offering enhanced reasoning, greater factual accuracy, and smoother integration with tools like code interpreters, retrieval systems, and image understanding. With native support for a 128K token context window, function calling, and robust tool usage, GPT-4.1 brings AI closer to behaving like a reliable, adaptive assistant—ready to work, build, and collaborate across tasks with speed and precision.


codex-mini-latest is OpenAI’s lightweight, high-speed AI coding model, fine-tuned from the o4-mini architecture. Designed specifically for use with the Codex CLI, it brings ChatGPT-level reasoning directly to your terminal, enabling efficient code generation, debugging, and editing tasks. Despite its compact size, codex-mini-latest delivers impressive performance, making it ideal for developers seeking a fast, cost-effective coding assistant.


codex-mini-latest is OpenAI’s lightweight, high-speed AI coding model, fine-tuned from the o4-mini architecture. Designed specifically for use with the Codex CLI, it brings ChatGPT-level reasoning directly to your terminal, enabling efficient code generation, debugging, and editing tasks. Despite its compact size, codex-mini-latest delivers impressive performance, making it ideal for developers seeking a fast, cost-effective coding assistant.


codex-mini-latest is OpenAI’s lightweight, high-speed AI coding model, fine-tuned from the o4-mini architecture. Designed specifically for use with the Codex CLI, it brings ChatGPT-level reasoning directly to your terminal, enabling efficient code generation, debugging, and editing tasks. Despite its compact size, codex-mini-latest delivers impressive performance, making it ideal for developers seeking a fast, cost-effective coding assistant.


GPT-4 Turbo is OpenAI’s enhanced version of GPT-4, engineered to deliver faster performance, extended context handling, and more cost-effective usage. Released in November 2023, GPT-4 Turbo boasts a 128,000-token context window, allowing it to process and generate longer and more complex content. It supports multimodal inputs, including text and images, making it versatile for various applications.


GPT-4 Turbo is OpenAI’s enhanced version of GPT-4, engineered to deliver faster performance, extended context handling, and more cost-effective usage. Released in November 2023, GPT-4 Turbo boasts a 128,000-token context window, allowing it to process and generate longer and more complex content. It supports multimodal inputs, including text and images, making it versatile for various applications.


GPT-4 Turbo is OpenAI’s enhanced version of GPT-4, engineered to deliver faster performance, extended context handling, and more cost-effective usage. Released in November 2023, GPT-4 Turbo boasts a 128,000-token context window, allowing it to process and generate longer and more complex content. It supports multimodal inputs, including text and images, making it versatile for various applications.


DeepSeek‑Coder V2 is an open-source, Mixture‑of‑Experts (MoE) code-focused variant of DeepSeek‑V2, purpose-built for code generation, completion, debugging, and mathematical reasoning. Trained with an additional 6 trillion tokens of code and text, it supports up to 338 programming languages and a massive 128K‑token context window, rivaling or exceeding commercial code models in performance.


DeepSeek‑Coder V2 is an open-source, Mixture‑of‑Experts (MoE) code-focused variant of DeepSeek‑V2, purpose-built for code generation, completion, debugging, and mathematical reasoning. Trained with an additional 6 trillion tokens of code and text, it supports up to 338 programming languages and a massive 128K‑token context window, rivaling or exceeding commercial code models in performance.


DeepSeek‑Coder V2 is an open-source, Mixture‑of‑Experts (MoE) code-focused variant of DeepSeek‑V2, purpose-built for code generation, completion, debugging, and mathematical reasoning. Trained with an additional 6 trillion tokens of code and text, it supports up to 338 programming languages and a massive 128K‑token context window, rivaling or exceeding commercial code models in performance.


DeepSeek R1 Distill refers to a family of dense, smaller models distilled from DeepSeek’s flagship DeepSeek R1 reasoning model. Released early 2025, these models come in sizes ranging from 1.5B to 70B parameters (e.g., DeepSeek‑R1‑Distill‑Qwen‑32B) and retain powerful reasoning and chain-of-thought abilities in a more efficient architecture. Benchmarks show distilled variants outperform models like OpenAI’s o1‑mini, while remaining open‑source under MIT license.


DeepSeek R1 Distill refers to a family of dense, smaller models distilled from DeepSeek’s flagship DeepSeek R1 reasoning model. Released early 2025, these models come in sizes ranging from 1.5B to 70B parameters (e.g., DeepSeek‑R1‑Distill‑Qwen‑32B) and retain powerful reasoning and chain-of-thought abilities in a more efficient architecture. Benchmarks show distilled variants outperform models like OpenAI’s o1‑mini, while remaining open‑source under MIT license.


DeepSeek R1 Distill refers to a family of dense, smaller models distilled from DeepSeek’s flagship DeepSeek R1 reasoning model. Released early 2025, these models come in sizes ranging from 1.5B to 70B parameters (e.g., DeepSeek‑R1‑Distill‑Qwen‑32B) and retain powerful reasoning and chain-of-thought abilities in a more efficient architecture. Benchmarks show distilled variants outperform models like OpenAI’s o1‑mini, while remaining open‑source under MIT license.


DeepSeek R1 Distill Qwen‑32B is a 32-billion-parameter dense reasoning model released in early 2025. Distilled from the flagship DeepSeek R1 using Qwen 2.5‑32B as a base, it delivers state-of-the-art performance among dense LLMs—outperforming OpenAI’s o1‑mini on benchmarks like AIME, MATH‑500, GPQA Diamond, LiveCodeBench, and CodeForces rating.


DeepSeek R1 Distill Qwen‑32B is a 32-billion-parameter dense reasoning model released in early 2025. Distilled from the flagship DeepSeek R1 using Qwen 2.5‑32B as a base, it delivers state-of-the-art performance among dense LLMs—outperforming OpenAI’s o1‑mini on benchmarks like AIME, MATH‑500, GPQA Diamond, LiveCodeBench, and CodeForces rating.


DeepSeek R1 Distill Qwen‑32B is a 32-billion-parameter dense reasoning model released in early 2025. Distilled from the flagship DeepSeek R1 using Qwen 2.5‑32B as a base, it delivers state-of-the-art performance among dense LLMs—outperforming OpenAI’s o1‑mini on benchmarks like AIME, MATH‑500, GPQA Diamond, LiveCodeBench, and CodeForces rating.

BoundaryML.com introduces BAML, an expressive language specifically designed for structured text generation with Large Language Models (LLMs). Its primary purpose is to simplify and enhance the process of obtaining structured data (like JSON) from LLMs, moving beyond the challenges of traditional methods by providing robust parsing, error correction, and reliable function-calling capabilities.

BoundaryML.com introduces BAML, an expressive language specifically designed for structured text generation with Large Language Models (LLMs). Its primary purpose is to simplify and enhance the process of obtaining structured data (like JSON) from LLMs, moving beyond the challenges of traditional methods by providing robust parsing, error correction, and reliable function-calling capabilities.

BoundaryML.com introduces BAML, an expressive language specifically designed for structured text generation with Large Language Models (LLMs). Its primary purpose is to simplify and enhance the process of obtaining structured data (like JSON) from LLMs, moving beyond the challenges of traditional methods by providing robust parsing, error correction, and reliable function-calling capabilities.

Chat01.ai is a platform that offers free and unlimited chat with OpenAI 01, a new series of AI models. These models are specifically designed for complex reasoning and problem-solving in areas such as science, coding, and math, by employing a "think more before responding" approach, trying different strategies, and recognizing mistakes.

Chat01.ai is a platform that offers free and unlimited chat with OpenAI 01, a new series of AI models. These models are specifically designed for complex reasoning and problem-solving in areas such as science, coding, and math, by employing a "think more before responding" approach, trying different strategies, and recognizing mistakes.

Chat01.ai is a platform that offers free and unlimited chat with OpenAI 01, a new series of AI models. These models are specifically designed for complex reasoning and problem-solving in areas such as science, coding, and math, by employing a "think more before responding" approach, trying different strategies, and recognizing mistakes.
This page was researched and written by the ATB Editorial Team. Our team researches each AI tool by reviewing its official website, testing features, exploring real use cases, and considering user feedback. Every page is fact-checked and regularly updated to ensure the information stays accurate, neutral, and useful for our readers.
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