Модели OpenAI

GPT-6 Luna is OpenAI’s efficient GPT-6 model for focused tasks and high-volume workloads. It accepts text and image inputs, supports a context window of about 1.05 million tokens and configurable reasoning effort, and can use built-in tools through the Responses API. Choose it for repeatable processing where latency and cost are important.

OpenAI reasoning model for coding, visual tasks and professional workflows, with long context and support for agents through compatible providers.

GPT-5.4 mini brings the main capabilities of GPT-5.4 to a faster and more efficient model optimized for high-volume workloads. It supports both text and image inputs, offering strong performance in reasoning, coding, and tool use while lowering latency and cost for large-scale deployment. The model is built for production environments that need the right balance between capability and efficiency, making it a strong fit for chat applications, coding assistants, and large-scale agent workflows. GPT-5.4 mini provides reliable instruction following, solid multi-step reasoning, and consistent results across a wide range of tasks with better cost efficiency.

GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series. It is suited for high-volume, latency-sensitive tasks such as chat, classification, and lightweight agentic workflows, providing capable reasoning for its price tier.

Text-Embedding-3-Large is OpenAI’s most capable embedding model, supporting both English and non-English text tasks. It produces high-dimensional embeddings (up to 3072 dimensions) for advanced semantic similarity, search, and clustering, and allows flexible trade-offs between performance and resource usage.

GPT-5.4 is OpenAI’s newest frontier model that merges the Codex and GPT families into a single unified system. It offers a 1M+ token context window (922K input, 128K output) and supports both text and image inputs, enabling high-context reasoning, coding, and multimodal analysis in one workflow. The model brings stronger performance in coding, document understanding, tool usage, and instruction following. It’s built to be a solid default for both general tasks and software engineering—able to produce production-ready code, synthesize information from multiple sources, and handle complex multi-step workflows with fewer iterations and better token efficiency.

GPT-6 Astra is OpenAI's flagship model for demanding end-to-end work. It is suited for advanced analysis, software engineering, deep research, scientific work, and document creation, with particular strengths in long-horizon agentic tasks that involve computer and browser use.

GPT-5.6 Terra is a balanced model in OpenAI's GPT-5.6 series, positioned between the flagship Sol tier and the cost-efficient Luna tier. It is suited for everyday coding, reasoning, and agentic tasks where capability and cost need to be balanced, offering strong performance at roughly half the cost of Sol.

GPT-5.6 Sol is the flagship model in OpenAI's GPT-5.6 series. It is suited for complex reasoning, coding, and agentic workflows, and is particularly strong at command-line and multi-step coding tasks and long-horizon problem solving.

GPT-5.5 Pro is OpenAI’s high-capability model optimized for deep reasoning and accuracy on complex, high-stakes workloads. It features a 1M+ token context window (922K input, 128K output) with support for text and image inputs, and is designed for long-horizon problem solving, agentic coding, and precise execution across multi-step workflows.

GPT-5.5 is OpenAI’s frontier model designed for complex professional workloads, building on GPT-5.4 with stronger reasoning, higher reliability, and improved token efficiency on hard tasks. It features a 1M+ token context window (922K input, 128K output) with support for text and image inputs, enabling large-scale reasoning, coding, and multimodal workflows within a single system.

GPT Image 2 is our state-of-the-art image generation model for fast, high-quality image generation and editing. It supports flexible image sizes and high-fidelity image inputs.

GPT-5.4 nano is the lightest and most cost-efficient model in the GPT-5.4 family, built for speed-sensitive and high-volume workloads. It supports both text and image inputs and is designed for low-latency tasks such as classification, data extraction, ranking, and sub-agent execution. The model is focused on responsiveness and efficiency rather than deep reasoning, making it ideal for pipelines that need fast and reliable results at scale. GPT-5.4 nano is a strong fit for background processing, real-time systems, and distributed agent architectures where keeping costs and latency low is essential.

GPT-5.4 Pro is OpenAI’s most capable model, extending GPT-5.4’s unified architecture with stronger reasoning for complex, high-stakes tasks. It includes a 1M+ token context window (922K input, 128K output) and supports both text and image inputs. Tuned for step-by-step reasoning, instruction following, and high accuracy, GPT-5.4 Pro stands out in agentic coding, long-context workflows, and multi-step problem solving.

GPT-5.3 Chat is an updated version of ChatGPT’s most widely used model, designed to make everyday conversations smoother, more practical, and more directly helpful. It provides more accurate answers with stronger context awareness and noticeably cuts down on unnecessary refusals, excessive caveats, and overly cautious wording that can disrupt the flow of conversation.

GPT-5.3-Codex is an OpenAI model optimized for agentic coding and long-running software engineering tasks. It is designed to inspect repositories, edit code, use development tools and verify its work across multiple steps. It accepts text and image inputs, supports structured outputs and function calling, and offers configurable reasoning effort.

GPT-5.2-Codex is an enhanced version of GPT-5.1-Codex, optimized for software engineering and coding tasks. Designed for both interactive sessions and longer, independent execution, it excels at building projects, developing features, debugging, large-scale refactoring, and code review. Compared to its predecessor, 5.2-Codex follows developer instructions more closely and delivers cleaner, higher-quality code. It integrates seamlessly with developer tools—CLI, IDEs, GitHub, and cloud platforms—and adapts its reasoning effort based on task complexity, providing quick responses for simple tasks and maintaining extended performance for larger projects. The model supports structured code reviews, detects critical flaws, validates behavior against tests, and handles multimodal inputs like images for UI work. It is specifically tailored for agentic coding applications.

GPT-Image-1.5 is the flagship image generation and editing model from OpenAI, designed for precise, natural, and fast creation. It reliably follows user instructions down to fine details, preserving critical elements like lighting, composition, and facial likeness across edits and generations. GPT-Image-1.5 excels at a wide range of editing tasks—including addition, removal, stylization, combination, and advanced text rendering—producing images that closely match user intent. With up to 4× faster generation speeds compared to previous versions, it streamlines creative workflows, enabling quick iterations whether you need a simple fix or a total visual transformation. Enhanced integration and lower API costs make GPT-Image-1.5 ideal for marketing, product visualization, ecommerce, and creative tools scenarios, while its dedicated editor and presets provide a delightful, accessible creative space for both practical and expressive image work.

GPT-5.2 Chat (also known as Instant) is the fast and lightweight version of the 5.2 family, built for low-latency chatting while maintaining strong general intelligence. It leverages adaptive reasoning to focus more “thinking” on challenging queries, boosting accuracy in math, coding, and multi-step tasks without sacrificing speed in everyday conversations. The model is naturally warmer and more conversational, with improved instruction following and more stable short-form reasoning. GPT-5.2 Chat is ideal for high-throughput, interactive scenarios where quick response and consistency are more important than in-depth analysis.

GPT-5.2 Pro is OpenAI's most advanced model, featuring significant upgrades in agentic coding and long-context capabilities compared to GPT-5 Pro. It is specifically optimized for handling complex tasks that demand step-by-step reasoning, precise instruction following, and accuracy in critical scenarios. The model supports advanced test-time routing and sophisticated prompt understanding, including user cues like "think hard about this." Key improvements include reduced hallucination and sycophancy, along with stronger performance in coding, writing, and health-related tasks.

GPT-5.2 is the newest frontier-level model in the GPT-5 line, providing enhanced agentic abilities and better long-context performance than GPT-5.1. It employs adaptive reasoning to dynamically distribute computational resources, enabling quick responses to simple requests and deeper analysis for complex challenges. Designed for wide-ranging tasks, GPT-5.2 offers steady improvements in mathematics, programming, science, and tool usage, delivering more coherent long-form responses and increased reliability when using tools.

GPT-5.1-Codex-Max is OpenAI’s newest agentic coding model, created for extended, high-context software development tasks. Built on an enhanced 5.1 reasoning stack, it’s been trained with agentic workflows covering software engineering, mathematics, and research. GPT-5.1-Codex-Max offers faster performance, better reasoning abilities, and increased token efficiency throughout the development process.

GPT-5.1-Codex-Mini is a smaller OpenAI model tuned for agentic coding in Codex-style environments. It favors lower latency and cost for focused changes, code review and routine developer tasks while retaining tool-assisted workflows. For work that needs deeper reasoning or sustained autonomy, use a larger Codex model.

GPT-5.1-Codex is an OpenAI model optimized for agentic software development in Codex and similar tool-driven environments. It can inspect code, plan and implement multi-file changes, and work through longer coding tasks with reasoning and tool calls. The model accepts text and image inputs and is available through the Responses API.

GPT-5.1 Chat (also known as Instant) is the fast, lightweight member of the 5.1 family, optimized for low-latency chat while retaining strong general intelligence. It uses adaptive reasoning to selectively “think” on harder queries, improving accuracy on math, coding, and multi-step tasks without slowing down typical conversations. The model is warmer and more conversational by default, with better instruction following and more stable short-form reasoning. GPT-5.1 Chat is designed for high-throughput, interactive workloads where responsiveness and consistency matter more than deep deliberation.

GPT-5.1 is the newest top-tier model in the GPT-5 series, featuring enhanced general reasoning, better instruction following, and a more natural conversational tone compared to GPT-5. With adaptive reasoning, it dynamically adjusts its computational effort—responding swiftly to simple queries and diving deeper into complex tasks. Explanations are now clearer and use less jargon, making challenging topics easier to grasp. Designed for a wide range of tasks, GPT-5.1 consistently improves performance in math, coding, and structured analysis, offering more cohesive long-form responses and more reliable tool usage. Its conversation style is warmer and more intuitive, yet still precise. GPT-5.1 stands as the main, fully capable successor to GPT-5.

GPT-5-Codex is a specialized version of GPT-5 tailored for software engineering and coding tasks. It is suitable for both interactive development sessions and the independent execution of complex engineering projects. The model is capable of building projects from scratch, developing new features, debugging, performing large-scale refactoring, and conducting code reviews. Compared to the standard GPT-5, Codex offers greater steerability, follows developer instructions more closely, and delivers cleaner, higher-quality code.

Whisper large-v3-turbo is a finetuned version of a pruned Whisper large-v3. In other words, it's the exact same model, except that the number of decoding layers have reduced from 32 to 4. As a result, the model is way faster, at the expense of a minor quality degradation.

GPT-5 Chat is tailored for advanced, natural, and context-aware conversations in enterprise environments. It leverages the latest advancements in OpenAI’s conversational AI, supporting multimodal and dynamic dialogue with enhanced context retention and user intent understanding.

The smallest and fastest member of the GPT-5 family, optimized for developer tools, rapid user interactions, and ultra-low latency environments. While it offers limited reasoning depth compared to larger models, GPT-5-Nano preserves essential instruction-following and safety mechanisms. It is the successor to GPT-4.1-nano and is best suited for real-time, cost-sensitive, or embedded applications.

A compact variant of GPT-5, designed for efficient handling of lighter-weight reasoning and conversational tasks. GPT-5 Mini retains the instruction-following and safety features of its larger counterpart, but with reduced latency and cost. It is the direct successor to OpenAI’s o4-mini model, making it ideal for scalable, cost-sensitive deployments.

OpenAI’s most advanced large language model, engineered for high-stakes applications requiring step-by-step reasoning, precise instruction following, and robust code generation. GPT-5 introduces major improvements in factual accuracy, user intent understanding, and hallucination reduction. It supports advanced prompt routing, user-specified intent (such as "think hard about this"), and is optimized for complex workflows in coding, writing, and health-related domains.

OpenAI’s 21B-parameter open-weight Mixture-of-Experts (MoE) model, released under the Apache 2.0 license. Features 3.6B active parameters per forward pass, optimized for low-latency inference and deployability on consumer or single-GPU hardware. Trained in OpenAI’s Harmony response format, it supports reasoning level configuration, fine-tuning, and agentic capabilities such as function calling and structured outputs.

An open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI, designed for high-reasoning, agentic, and general-purpose production use cases. Activates 5.1B parameters per forward pass and is optimized for single H100 GPU deployment with native MXFP4 quantization. Supports configurable reasoning depth, full chain-of-thought access, and native tool use, including function calling, browsing, and structured output generation.

The April 2023 release of GPT-4 Turbo, supporting vision, JSON mode, and function calling. Trained on data up to April 2023, optimized for advanced multimodal tasks.

The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. Trained with large-scale reinforcement learning for chain-of-thought reasoning, it is optimized for math, science, programming, and other STEM tasks, consistently achieving PhD-level accuracy on industry benchmarks.

GPT-4.1, a flagship model for advanced instruction following, software engineering, and long-context reasoning. Supports a 1 million token context window and is tuned for precise code diffs, agent reliability, and high recall in large document contexts.

GPT-4o (“o” for “omni”) is OpenAI’s latest multimodal model, supporting both text and image inputs with text outputs. Delivers improved performance in non-English languages and visual understanding, while being faster and more cost-effective than previous models.

The latest GPT-4 Turbo model with vision capabilities, supporting JSON mode and function calling. Trained on data up to December 2023, it is optimized for high-throughput, multimodal applications.

Preview release of GPT-4, featuring improved instruction following, JSON mode, reproducible outputs, and parallel function calling. Trained on data up to December 2023. Heavily rate-limited while in preview.

Experimental mini version of OpenAI’s o1 model, optimized for STEM tasks with efficient performance. Not recommended for production use and may be heavily rate-limited.

The August 2024 version of GPT-4o, offering improved structured output capabilities, including support for JSON schema in responses. Maintains high intelligence and efficiency, with enhanced non-English and visual performance.

Omni-Moderation is OpenAI’s newest multimodal content moderation model, available through the Moderation API. It is designed to identify potentially harmful content in both text and images, offering improved accuracy and granular control, especially in non-English languages.

A fine-tuned version of o4-mini, specifically optimized for use in Codex CLI. Recommended for code-related tasks, with improved performance in code generation and completion.

A speech-to-text model using GPT-4o for transcribing audio. It offers improved word error rate, better language recognition, and higher accuracy compared to the original Whisper models. Use it for more precise transcripts.

A well-rounded, powerful model from OpenAI, setting new standards in math, science, coding, and visual reasoning. Excels at technical writing and instruction-following, and is designed for multi-step problem solving across text, code, and images. BYOK is required for access.

Text-Embedding-3-Small is OpenAI’s efficient, compact embedding model, designed to convert text into numerical representations for semantic tasks such as search, clustering, and recommendations. It offers improved performance and cost-effectiveness compared to previous models, with low latency and storage requirements.

Specialized GPT-4o variant trained for web search understanding and execution within chat completions, enabling advanced search query comprehension.

Whisper Large v3 is OpenAI’s state-of-the-art model for automatic speech recognition (ASR) and speech translation. Trained on over 5 million hours of labeled data, it demonstrates strong generalization across datasets and domains, excelling in zero-shot transcription and translation tasks.

A compact reasoning model in OpenAI’s o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. Supports tool use and demonstrates competitive reasoning and coding performance across benchmarks, outperforming its predecessor o3-mini and approaching o3 in some domains. Well-suited for high-throughput scenarios where latency or cost is critical.

The continually updated version of OpenAI ChatGPT 4o, always pointing to the current GPT-4o model used by ChatGPT. Incorporates additional RLHF and may differ from the API version. Intended for research and evaluation, not recommended for production as it may be redirected or removed in the future.

DALL-E 3 is OpenAI’s third-generation text-to-image model, offering enhanced detail, accuracy, and the ability to understand complex prompts. It excels at generating realistic and creative images, handling intricate details like text and human anatomy, and supports various aspect ratios for flexible output.

The fastest and most cost-effective model in the GPT-4.1 series, designed for tasks demanding low latency such as classification and autocompletion. Maintains a 1 million token context window and delivers exceptional performance at a small size, outperforming even some larger models on key benchmarks.

A mid-sized GPT-4.1 model delivering performance competitive with GPT-4o at substantially lower latency and cost. Retains a 1 million token context window and demonstrates strong coding ability and vision understanding, making it suitable for interactive applications with tight performance constraints.

A cost-efficient language model from OpenAI, optimized for STEM reasoning tasks, especially in science, mathematics, and coding. Supports the `reasoning_effort` parameter for adjustable thinking time and features significant improvements over its predecessor, with better performance on complex questions and lower latency and cost.

OpenAI’s new state-of-the-art image generation model. This is a natively multimodal language model that accepts both text and image inputs and produces image outputs. It powers image generation in ChatGPT, offering exceptional prompt adherence, a high level of detail, and quality.

OpenAI’s most advanced small model, GPT-4o mini, supports both text and image inputs with text outputs. It is highly cost-effective, achieving SOTA intelligence and outperforming larger models on key benchmarks, making it ideal for scalable, interactive applications.

The November 2024 release of GPT-4o, featuring enhanced creative writing, more natural and engaging responses, and improved file handling. Maintains the intelligence of GPT-4 Turbo while being twice as fast and 50% more cost-effective, with better support for non-English languages and visual tasks.

A text-to-speech model built on GPT-4o mini, a fast and powerful language model. Use it to convert text into natural-sounding spoken audio.

A flagship large language model from OpenAI, optimized for advanced instruction following, real-world software engineering, and long-context reasoning. Supports a 1 million token context window and outperforms GPT-4o and GPT-4.5 in coding (54.6% SWE-bench Verified), instruction compliance (87.4% IFEval), and multimodal understanding. Tuned for precise code diffs, agent reliability, and high recall in large document contexts, making it ideal for agents, IDE tooling, and enterprise knowledge retrieval.

GPT-6 Sol is OpenAI’s reasoning model for demanding coding and agentic workflows, balancing capability and cost within the GPT-6 family. It accepts text and image inputs and supports a context window of about 1.05 million tokens. Reasoning effort can be set from none through max; the Responses API supports built-in tools and function calling for multi-step tasks.

GPT Image 2.5 Flare is OpenAI’s speed-focused image model for everyday generation and editing. It accepts text prompts and image references, follows detailed visual instructions and supports a range of output sizes and quality settings. This is the fast variant of GPT Image 2.5; Sunburst is a separate model for greater editing precision.

GPT Image 2.5 Sunburst is OpenAI’s quality-focused image model for generation and editing. It accepts text and image references and is designed for precise visual changes, subject preservation and demanding image production. It is a separate variant from the faster Flare model, with multiple output sizes and quality settings.