List of the Top Foundation Models for Oh My OpenAgent in 2026

GPT-6 Astra is OpenAI’s advanced frontier model for computer use, coding, browsing, scientific research, cybersecurity, professional knowledge work, and long-running agentic tasks. It is designed to combine high-level reasoning with the ability to directly operate software and tools rather than only generating text responses. Astra can navigate websites, complete forms, update business systems, organize calendars, conduct research, analyze data, generate plots, test applications, and troubleshoot problems that appear on screen. For professional users, the model can create documents, spreadsheets, presentations, analyses, websites, and other artifacts while following existing templates, formatting requirements, and organizational styles. Its software engineering capabilities include codebase analysis, implementation, debugging, verification, browser testing, system configuration, and other terminal-based development workflows. In Codex, Astra can preserve notes across context windows and search earlier requirements, test results, messages, and tool outputs during lengthy development sessions. The model also combines scientific reasoning with computer use so researchers can work with specialized applications, inspect data, explore results, and assist with computational research processes. OpenAI reports substantial advances in Astra’s cybersecurity capabilities, while the production model applies safeguards to restrict higher-risk activities such as advanced exploit creation. Alignment improvements focus on interpreting user intent, respecting authorization boundaries, avoiding attempts to circumvent system restrictions, and communicating more accurately about what the model can and cannot do. GPT-6 Astra supports enterprise-oriented deployment features including eligible Zero Data Retention API configurations and is available through ChatGPT, the OpenAI API, Amazon Web Services, and Amazon Bedrock.

GPT-6 Luna is OpenAI’s efficiency-focused GPT-6 model for developers and users who need capable reasoning, coding, computer use, and agentic workflows at very low inference cost. It is positioned below GPT-6 Sol and GPT-6 Astra in the model family while bringing many of the GPT-6 generation’s improvements to applications that prioritize scale and affordability. The model supports configurable reasoning effort so developers can allocate additional computation to complex tasks while keeping simpler interactions fast and economical. GPT-6 Luna can power business automation across applications used for sales, marketing, finance, operations, customer support, and human resources. Its coding capabilities support work on real software repositories, including multi-step engineering tasks that require analysis, modification, testing, and iteration. Luna can also operate in computer-use environments, allowing agents to navigate graphical interfaces and complete extended workflows across software applications. OpenAI reports that GPT-6 Luna substantially improves factual reliability compared with GPT-5.6 Luna and can approach the capabilities of more expensive models on some tasks when used at higher reasoning levels. The model also benefits from GPT-6’s improved collaboration style, with clearer technical communication, less unnecessary jargon, and fewer low-value details. Enhanced prompt caching allows applications to reuse previously processed context at a discount while preserving cache reuse when reasoning effort or available tools change. These efficiency improvements make Luna suitable for high-volume agents, coding assistants, automated workflows, customer-facing applications, and other systems where per-request cost is important. GPT-6 Luna is available through the OpenAI API as gpt-6-luna, as well as through ChatGPT Work, Codex, and supported ChatGPT desktop experiences.

GPT-6 Sol is an advanced OpenAI model positioned between the cost-efficient GPT-6 Luna and the higher-capability GPT-6 Astra for demanding professional and agentic workloads. The model is designed for coding, knowledge work, business automation, computer use, research, and other tasks that require sustained reasoning across multiple steps. It inherits advances from the GPT-6 generation while emphasizing a balance of intelligence, speed, and operating cost for applications that need to run at scale. GPT-6 Sol supports multiple reasoning-effort levels so applications can spend more computation on difficult tasks and reduce effort for straightforward requests. In software development, it can handle complex real-codebase tasks, generate merge-ready changes, debug software, work through terminal workflows, and operate as part of coding agents. Its professional-work capabilities support multi-application processes spanning functions such as finance, operations, sales, marketing, customer support, and human resources. Computer-use abilities allow agents powered by GPT-6 Sol to interact with graphical interfaces and complete long-horizon workflows involving everyday and professional software. OpenAI has also improved the model’s factual reliability, communication style, and alignment compared with GPT-5.6 Sol, including lower rates of misleading claims in challenging coding evaluations. GPT-6 prompt caching provides higher cache-hit rates, supports changing reasoning effort or available tools without invalidating earlier cached context, and offers substantial discounts for cached input tokens. Developers can monitor caching behavior, configure prompt-cache breakpoints, and incorporate Sol into persistent agents that repeatedly reuse large amounts of context. GPT-6 Sol is accessible through ChatGPT Work, Codex, and the OpenAI API under the gpt-6-sol model identifier.

GPT-5.6 Terra is a balanced model in OpenAI’s GPT-5.6 series, designed to provide strong performance for everyday work while keeping costs lower than the flagship Sol tier. The GPT-5.6 family includes Sol for the highest capability, Terra for balanced work, and Luna for fast and affordable use cases. Terra is positioned as a practical option for developers, businesses, and enterprise teams that need capable reasoning, coding, automation, research support, and defensive security assistance without always using the most expensive model. According to the pasted preview text, Terra offers competitive performance to GPT-5.5 while being 2x cheaper. It appears in GPT-5.6 benchmark previews for Terminal-Bench 2.1, GeneBench v1, ExploitBench, and ExploitGym, showing that the model is intended for technical and long-horizon tasks as well as general work. Terra can support coding workflows that require planning, iteration, command-line reasoning, and tool coordination. It can also support legitimate cybersecurity workflows such as code review, vulnerability research, patch development, debugging, security education, and defensive testing. The model is developed with layered safeguards matched to its capabilities, including trained refusals, real-time checks, misuse classifiers, monitoring, enforcement, and account-level review. OpenAI also describes automated red-teaming and third-party human expert red-teaming as part of the broader GPT-5.6 safety process. Terra is priced below Sol in the pasted API pricing structure, with lower input and output costs per 1 million tokens. GPT-5.6 Terra helps organizations use a capable GPT-5.6 model for production workflows where performance, cost efficiency, and safety controls all matter.

Kimi K3 is Moonshot AI’s most advanced model, designed for high-end reasoning, software engineering, multimodal understanding, knowledge work, and agentic AI applications. The model has 2.8 trillion parameters and is built on Kimi Delta Attention, a hybrid linear attention mechanism created for long-context performance. It also uses Attention Residuals and supports a native context window of up to 1 million tokens. This makes Kimi K3 suitable for tasks involving large codebases, long research materials, enterprise documentation, multi-file analysis, legal documents, technical manuals, and complex workflows. Kimi K3 always has thinking mode enabled, with reasoning effort configured through the reasoning_effort field and maximum effort currently supported as the default. Developers can use the model through an OpenAI-compatible API, making it easier to integrate with existing SDKs, clients, and application infrastructure. The model supports streaming responses with separate reasoning and final-answer deltas, allowing applications to display reasoning progress and final content differently. Kimi K3 also supports strict structured output with JSON Schema, partial mode for continuing from a prefix, custom tool calling, required tool use, and dynamic tool loading through system messages. Its vision capabilities support image and video inputs through base64 or uploaded files, enabling analysis of visual content alongside text. Automatic context caching helps workflows that reuse long prefixes, such as large knowledge bases or persistent system context, without requiring developers to manage cache IDs manually. By combining frontier-scale parameters, long-context processing, visual input, structured outputs, tool orchestration, and developer-friendly API compatibility, Kimi K3 gives teams a strong foundation for advanced AI agents, coding assistants, research systems, enterprise automation, and multimodal applications.

GPT-5.6 Luna is the lowest-cost model in OpenAI’s GPT-5.6 family, built for fast and affordable AI assistance across everyday and technical workflows. The GPT-5.6 lineup includes Sol as the flagship model, Terra as the balanced model for everyday work, and Luna as the efficient model for users who need strong capability at lower cost. Luna is intended for developers, businesses, and teams that need scalable AI for coding help, workflow automation, research support, analysis, customer-facing applications, and high-volume API usage. In the pasted preview text, Luna is presented as part of the same GPT-5.6 release process and benchmark set as Sol and Terra. It appears in evaluations for command-line coding workflows, long-horizon biology tasks, ExploitBench, and ExploitGym, indicating that it is designed to handle more than simple chat use cases. The model is priced at a lower per-token rate than Sol and Terra, making it more suitable for applications where cost efficiency is a major priority. GPT-5.6 Luna also supports the new GPT-5.6 prompt caching approach, including explicit cache breakpoints, a 30-minute minimum cache life, cache writes billed above the uncached input rate, and discounted cached-input reads. Like the rest of the GPT-5.6 family, Luna is developed with layered safeguards matched to model capability. These safeguards include trained refusals for prohibited cyber assistance, real-time misuse classifiers, paused generation for higher-risk cases, account-level review, monitoring, enforcement, automated red-teaming, and third-party human expert red-teaming. Luna is expected to support legitimate defensive and technical workflows such as code review, debugging, patch development, security education, and defensive testing while making prohibited misuse more difficult and detectable. GPT-5.6 Luna helps organizations deploy GPT-5.6-class AI where speed, affordability, scalability, and safe production use are the most important requirements.

GPT-5.5 represents a new class of AI built to transform how work is done across digital environments. It combines advanced reasoning, tool usage, and task execution capabilities to manage complex, multi-step workflows with minimal human intervention. The model performs strongly in software engineering, data analysis, business operations, and scientific research, where it can plan tasks, gather information, test solutions, and refine outputs iteratively. It supports generating documents, building applications, analyzing large datasets, and navigating software systems as part of a unified workflow. A key capability is its integration with workspace agents—customizable AI agents that can be created once and deployed across teams to automate entire processes. These agents can run continuously, interact with tools like CRM systems, messaging platforms, and document editors, and keep workflows moving without constant supervision. Organizations can define permissions, approval checkpoints, and monitoring to maintain full control over automation. GPT-5.5 also improves collaboration by standardizing workflows and scaling best practices across teams. With enterprise-grade security and governance, it is designed for safe deployment in complex environments. Its ability to persist through ambiguity and long-running tasks makes it highly effective for execution-heavy work. By reducing manual intervention and increasing speed, GPT-5.5 enables teams to focus on higher-value activities and operate at a significantly higher level of productivity.

GPT-6.1 Sol is OpenAI's upgraded Sol model for developers and professionals who need advanced reasoning and agentic capabilities without the higher cost of GPT-6 Astra. It is designed for coding, professional knowledge work, computer use, scientific research, factual question answering, and multi-step business workflows. OpenAI describes GPT-6.1 Sol as approaching GPT-6 Astra's intelligence across several important workloads while charging one-fifth of Astra's standard input and output token prices. On DeepSWE v1.1, which evaluates long-horizon software engineering in real codebases, GPT-6.1 Sol matches GPT-6 Astra at approximately one-fifth of the cost and exceeds GPT-6 Sol's best score by 6.4 percentage points. Its professional-work capabilities include understanding complex PDFs containing tables, charts, diagrams, and fine-print details across fields such as finance, healthcare, and legal work. On AutomationBench, GPT-6.1 Sol improves on GPT-6 Sol by 4.8 percentage points at the same reasoning setting and scores 2.2 points above Opus 5.5 at medium reasoning effort. Computer-use performance also advances significantly, with GPT-6.1 Sol outperforming GPT-6 Sol by seven percentage points on the OSWorld 2.0 offline set at maximum reasoning effort and coming within 2.1 points of GPT-6 Astra. For scientific research, the model can work with code and terminal tools on workflows involving data analysis, simulations, model fitting, and theorem proving, more than doubling GPT-6 Sol's Terminal-Bench Science 0.1 score at maximum effort. OpenAI also reports improved factual accuracy, including a reduction in the factual-error rate from 11.4% with GPT-6 Sol to 7.7% with GPT-6.1 Sol at low reasoning effort on its deliberately difficult factuality evaluation.

Kimi K2.5 is an advanced multimodal AI model engineered for high-performance reasoning, coding, and visual intelligence tasks. It natively supports both text and visual inputs, allowing applications to analyze images and videos alongside natural language prompts. The model achieves open-source state-of-the-art results across agent workflows, software engineering, and general-purpose intelligence tasks. With a massive 256K token context window, Kimi K2.5 can process large documents, extended conversations, and complex codebases in a single request. Its long-thinking capabilities enable multi-step reasoning, tool usage, and precise problem solving for advanced use cases. Kimi K2.5 integrates smoothly with existing systems thanks to full compatibility with the OpenAI API and SDKs. Developers can leverage features like streaming responses, partial mode, JSON output, and file-based Q&A. The platform supports image and video understanding with clear best practices for resolution, formats, and token usage. Flexible deployment options allow developers to choose between thinking and non-thinking modes based on performance needs. Transparent pricing and detailed token estimation tools help teams manage costs effectively. Kimi K2.5 is designed for building intelligent agents, developer tools, and multimodal applications at scale. Overall, it represents a major step forward in practical, production-ready multimodal AI.

Kimi K2.6 is a cutting-edge agentic AI model developed by Moonshot AI, designed to improve practical application, programming efficiency, and complex reasoning abilities beyond its forerunners, K2 and K2.5. Utilizing a Mixture-of-Experts framework, this model embodies the multimodal, agent-centric principles of the Kimi series, seamlessly combining language understanding, coding skills, and tool application into a unified system capable of planning and executing sophisticated workflows. It boasts advanced reasoning capabilities and superior agent planning, allowing it to break down tasks, coordinate multiple tools, and address challenges involving numerous files or steps with heightened accuracy and efficiency. Furthermore, it excels in tool-calling functions, ensuring a reliable connection with external platforms like web searches or APIs, while incorporating built-in validation systems to confirm the correctness of execution formats. Significantly, Kimi K2.6 marks a transformative advancement in the AI landscape, establishing new benchmarks for the intricacy and dependability of automated processes, and paving the way for future innovations in the field.

GPT-5.5 Pro represents a new class of AI designed to transform how work gets done across digital environments. It combines advanced reasoning, tool usage, and task execution capabilities to handle complex, multi-step workflows with minimal human intervention. The model excels in areas such as software engineering, data analysis, business operations, and scientific research, where it can plan tasks, gather information, test solutions, and refine outputs continuously. It supports creating applications, generating reports, building spreadsheets, and navigating software systems as part of a complete workflow. A key capability is its integration with workspace agents—custom AI agents that can be built once and deployed across teams to automate entire processes. These agents can run tasks on schedules, interact with tools like CRM systems, messaging platforms, and document editors, and keep workflows moving without constant supervision. Organizations can define permissions, approval checkpoints, and monitoring to maintain control over automated processes. GPT-5.5 Pro also enhances collaboration by enabling teams to standardize workflows and scale best practices across the organization. With enterprise-grade security and governance, it ensures safe deployment in complex environments. Its ability to persist through ambiguity and long tasks makes it highly effective for execution-heavy work. By reducing manual intervention and increasing speed, it allows teams to focus on higher-value activities. Ultimately, GPT-5.5 Pro enables businesses and professionals to operate at a significantly higher level of productivity and efficiency.

Gemini 3.1 Pro is Google’s latest advancement in the Gemini 3 model series, engineered to tackle complex tasks that demand deeper reasoning and analytical rigor. As the upgraded core intelligence behind recent breakthroughs like Gemini 3 Deep Think, it strengthens the foundation for advanced applications across science, engineering, business, and creative work. The model achieved a verified score of 77.1% on ARC-AGI-2, a benchmark designed to test novel logic problem-solving, more than doubling the reasoning performance of its predecessor, Gemini 3 Pro. This improvement reflects its ability to approach unfamiliar challenges with structured thinking rather than surface-level responses. Gemini 3.1 Pro is designed for tasks where simple outputs are not enough, enabling detailed synthesis, data consolidation, and strategic planning. It also supports creative and technical workflows, such as generating clean, production-ready animated SVG graphics directly from text prompts. Because these graphics are generated as pure code rather than pixel-based media, they remain lightweight, scalable, and web-optimized. Developers can access Gemini 3.1 Pro in preview through the Gemini API, Google AI Studio, Gemini CLI, Antigravity, and Android Studio. Enterprise users can integrate it via Gemini Enterprise Agent Platform and Gemini Enterprise for large-scale deployment. Consumers gain access through the Gemini app and NotebookLM, with expanded limits for Google AI Pro and Ultra subscribers. The preview release allows Google to gather feedback and further refine agentic workflows before broader availability. Overall, Gemini 3.1 Pro establishes a stronger baseline for intelligent, real-world problem solving across consumer, developer, and enterprise environments.

GPT-5.4 is a frontier artificial intelligence model developed by OpenAI to perform complex reasoning, coding, and knowledge-based tasks. It is designed to support professionals across industries by helping them automate workflows, analyze information, and produce detailed work outputs. The model integrates advanced reasoning capabilities with powerful coding performance derived from earlier Codex systems. GPT-5.4 can generate and edit documents, spreadsheets, presentations, and structured data used in business operations. One of its major improvements is its ability to interact with tools and external systems to complete multi-step workflows across different applications. This capability allows AI agents built on GPT-5.4 to perform tasks such as data entry, research, and automated software interactions. The model also supports extremely large context windows, enabling it to process long documents and maintain awareness across extended tasks. Improved visual understanding allows GPT-5.4 to interpret images, screenshots, and complex documents more effectively. It also introduces better web browsing and research capabilities for locating and synthesizing information online. Compared with previous versions, GPT-5.4 reduces factual errors and produces more consistent responses. Developers can access the model through APIs and integrate it into software applications, automation systems, and enterprise workflows. Overall, GPT-5.4 represents a significant step forward in AI capabilities for knowledge work, software development, and intelligent automation.