OpenAI Unveils GPT-5-Codex: A Game-Changer in AI-Powered Coding

OpenAI upgrades Codex with a new version of GPT-5 | TechCrunch

OpenAI announced Monday that it's releasing a new version of GPT-5 to its AI coding agent, Codex. The company says its new model, called GPT-5-Codex, spends its "thinking" time more dynamically than previous models, and could spend anywhere from a few seconds to seven hours on a coding task. As a result, it performs better on agentic coding benchmarks. The new model is now rolling out in Codex products -- which can be accessed via a terminal, IDE, GitHub, or ChatGPT -- to all ChatGPT Plus, Pro, Business, Edu, and Enterprise users. OpenAI says it plans to make the model available to API customers in the future. The update is part of OpenAI's effort to make Codex more competitive with other AI coding products, such as Claude Code, Anysphere's Cursor, or Microsoft's GitHub Copilot. The market for AI coding tools has become much more crowded in the last year, as a result of intense user demand. Cursor surpassed $500 million in ARR earlier in 2025 and Windsurf, a similar code editor, was the subject of a chaotic acquisition attempt that saw its team split between Google and Cognition. OpenAI says that GPT-5-Codex outperforms GPT-5 on SWE-bench Verified, a benchmark measuring agentic coding abilities, as well as a benchmark measuring performance on code refactoring tasks from large, established repositories. The company also says it trained GPT-5-Codex for conducting code reviews, and asked experience software engineers to evaluate the model's review comments. The engineers reportedly found GPT-5-Codex to submit fewer incorrect comments, while adding more "high-impact comments." In a briefing, OpenAI's Codex product lead Alexander Embiricos said that much of the increased performance was thanks to GPT-5-Codex's dynamic "thinking abilities." Users may be familiar with GPT-5's router in ChatGPT, which directs queries to different models based on the complexity of a task. Embiricos said GPT-5-Codex works similarly, but has no router under the hood, and can adjust for how long to work on a task in real-time. Embiricos says this is an advantage compared to a router, which decides how much computational power and time to use on a problem at the outset. Instead, GPT-5-Codex can decide five minutes into a problem that it needs to spend another hour. Embiricos said he's seen the model take upwards of seven hours in some cases.

OpenAI's new GPT-5 Codex model takes on Claude Code

OpenAI is rolling out the GPT-5 Codex model to all Codex instances, including Terminal, IDE extension, and Codex Web (chatgpt.com/codex). Codex is an AI agent that allows you to automate coding-related tasks. You can delegate your complex tasks to Codex and watch it execute code for you. Even if you don't know programming languages, you can use Codex to "vibe code" your apps and web apps. But so far, it has fallen a bit short of Claude Code, which is the market leader in the AI coding space. Today, OpenAI confirmed it's rolling out the Codex-special GPT-5 model. In a blog post, OpenAI stated the GPT-5 Codex model excels in real-world coding tasks, achieving a 74.5% success rate on the SWE-bench Verified benchmark. In code refactoring evaluations, it improved from 33.9% with GPT-5 to 51.3% with GPT-5-Codex. GPT-5-Codex is still rolling out. I don't see it on my Terminal yet, even though I pay for ChatGPT Plus ($20). OpenAI says it will be fully rolled out to everyone in the coming days.

OpenAI unveils new model GPT-5-Codex optimized for 'agentic coding'

OpenAI is rolling out GPT-5-Codex, a new, fine-tuned version of its GPT-5 model designed specifically for software engineering tasks in its AI-powered coding assistant, Codex. The release is part of a broader set of product updates that OpenAI says will help unify its Codex AI assistant across developers' terminals, integrated development environments (IDEs), GitHub, web, and the ChatGPT app. As of today, September 15, GPT-5-Codex becomes the default engine for cloud tasks and code review, with developers able to use it locally through the Codex command line interface (CLI) and IDE extension. The company said it would add the model as an option to the dozens already available in its application programming interface (API) at an unspecified future time, which would enable developers to build their own applications atop it or pipe it into existing ones more easily. Codex has steadily evolved since the company first introduced its CLI in April and web version in May. Two weeks ago, OpenAI consolidated these into a single product experience linked to ChatGPT accounts, enabling developers to switch seamlessly between local and cloud environments without losing context. GPT-5-Codex now extends this unified setup with deeper engineering capabilities. What GPT-5-Codex Brings to the Table Unlike GPT-5, which is built as a general-purpose AI model, GPT-5-Codex is optimized for what OpenAI calls "agentic coding," essentially where the AI agent functions as an autonomous colleague to a developer and can go off and code, run code, and make alterations all on its own for up to hours at a time. It sounds vaguely similar, though distinct enough, from the "agentic swarm" trend that VentureBeat founder Matt Marshall wrote about last week, in which human users can harness multiple agents with defined roles (3 or more) to collaborate on software writing and testing projects all on their own. As for GPT-5 Codex, OpenAI says it was trained on real-world engineering work, from debugging and adding tests to building projects from scratch and executing large-scale refactors. The model is also trained specifically for code review, where it can navigate codebases, reason over dependencies, and run tests to validate correctness. One of the model's key design features is adaptive thinking: that is, GPT-5-Codex adjusts how long it spends reasoning based on the complexity of the task. For short interactions, such as bug fixes or quick Q&A, it responds more quickly than earlier versions. For more demanding projects, it is able to run independently for extended periods -- in testing, it successfully executed refactor jobs lasting more than seven hours, iterating until it delivered a working implementation. But don't get it twisted: GPT-5-Codex does not rely on a router to switch between sub-models. Instead, the model itself dynamically decides how much "thinking" to do at training time. This lets it adjust mid-task if needed, for example revising a plan halfway through execution. For developers, that translates into more consistent handling of both short and long tasks without manual tweaking. In daily use, OpenAI says engineers have relied on Codex for reviewing pull requests, debugging, adding new features, and refactoring existing code. The company reports that GPT-5-Codex has already been integrated into internal review processes, catching hundreds of issues each day. Prior to this announcement, Codex was already running on GPT-5, the general-purpose model, for about the past month. With today's launch, GPT-5-Codex becomes available as a specialized variant trained specifically for coding tasks inside Codex. This marks a shift from a general AI model powering Codex to one purpose-built for agentic software engineering. Updates Across Codex Alongside the new model, OpenAI is releasing enhancements to the broader Codex product: * Codex CLI: Now rebuilt around agentic workflows, the CLI allows developers to attach images like wireframes or screenshots directly, share context, and track progress with built-in to-do lists. It includes simplified approval modes, improved formatting for tool calls and diffs, and support for longer sessions. OpenAI has open-sourced the CLI, which means teams can inspect or extend the harness that connects the model to developer environments. The company sees this as key to helping other organizations align product development with research improvements. * Codex IDE extension: Available in VS Code, Cursor, and similar forks, the extension enables developers to preview local changes and edit code with Codex inside their editor. It maintains context when moving tasks between cloud and local environments, allowing smoother collaboration. According to OpenAI, the IDE extension has quickly become the most popular way to use Codex, reflecting developers' preference for working directly alongside their code. * Codex cloud environment: Behind the scenes, OpenAI has made infrastructure improvements that reduce median completion times by 90 percent. The cloud agent can now auto-configure its environment, install dependencies as needed, and handle screenshots for UI work. Developers can delegate frontend tasks, and Codex will spin up a browser, inspect progress, and attach screenshots to GitHub pull requests. A new feature launching with GPT-5-Codex also enables Codex to output its own screenshots directly within web tasks, giving developers visual confirmation of results without needing to run code locally. * Code review automation: Once enabled in a GitHub repository, Codex automatically reviews pull requests as they progress, flagging issues and even implementing suggested fixes within the same review thread. Developers can also request specialized reviews, such as checks for security vulnerabilities. Codex's review process differs from static analyzers in that it takes a full copy of the codebase, reasons across dependencies, and runs tests before posting feedback -- a level of diligence that even thorough human reviewers may not always apply. Developer Experiences Early customers highlight how Codex is reshaping their workflows. Aaron Wang, Senior Software Engineer at Duolingo, noted that it outperformed other tools in backend code review benchmarks, catching compatibility issues and bugs that others missed. Richard Masters, VP Data & AI at Virgin Atlantic, described how his team can now leave a simple comment in a pull request and Codex will generate a clean update almost instantly, reducing back-and-forth cycles. At Cisco Meraki, Tech Lead Tres Wong-Godfrey used Codex to handle a complex refactor for another team's codebase, freeing him to focus on other priorities while Codex delivered tested, high-quality code. Kevin Royer, Senior AI/ML Engineer at Vanta, said Codex helps him maintain flow by taking on tasks in the background and returning clean diffs. Austin Ray, who leads the AI Dev X team at Ramp, reported that Codex caught an active bug other review tools had missed. Internally, OpenAI teams use Codex across domains like security, frontend, and infrastructure, treating it as a teammate for daily development. Usage of Codex has grown tenfold in the past month, reflecting both external adoption and heavier reliance inside the company itself. Safety and Controls OpenAI emphasizes that Codex runs in a sandboxed environment with network access disabled by default, whether in the cloud or locally. Developers can grant permissions for additional capabilities, such as web search or external tool connections, but are encouraged to review Codex's output before deploying. Each task comes with logs, test results, and citations to help ensure accuracy. The company also classifies GPT-5-Codex as "high capability" in sensitive domains such as biology and chemistry, and has implemented safeguards to minimize associated risks. Procurement teams may note that Codex is not positioned as a replacement for human review but as an additional layer of diligence. OpenAI recommends keeping Codex as a reviewer alongside human engineers, particularly for critical production systems. Pricing and Availability Codex is already bundled with OpenAI's paid subscription ChatGPT Plus ($20/month), Pro ($200/month), Business ($25), as well as Edu and Enterprise plans (no public pricing -- interested parties need to contact OpenAI for pricing). Usage scales by tier: Plus, Edu, and Business plans cover a limited number of focused sessions with the new model per week; Pro supports a full week of development across multiple projects; Business offers add-on credits for expanded use; and Enterprise provides a shared credit pool for large teams. For Plus users, limits are structured around a handful of coding sessions per week, while Pro users should rarely encounter limits in normal use. OpenAI has acknowledged developer feedback on wanting better visibility into usage caps and is considering more transparent indicators in future updates. With GPT-5-Codex, OpenAI positions Codex as more than just an autocomplete or debugging tool. By adapting to tasks of different sizes, working autonomously when needed, and integrating tightly into developer workflows, the company aims to provide a consistent coding partner across environments. Importantly, OpenAI does not intend for Codex to compete with tab-completion tools like GitHub Copilot. Instead, the company views Codex as complementary, with many developers using both -- one for keystroke-level acceleration, the other for higher-level task delegation.

OpenAI debuts GPT-5-Codex model to automate time-consuming coding tasks

OpenAI debuts GPT-5-Codex model to automate time-consuming coding tasks OpenAI today introduced a new artificial intelligence model, GPT-5-Codex, that it says can complete hours-long programming tasks without user assistance. The algorithm is an improved version of GPT-5 trained on additional coding data. It's accessible through Codex, an AI programming tool included in paid ChatGPT plans. OpenAI says that GPT-5-Codex is better than its predecessor at complex, time-consuming programming tasks. "During testing, we've seen GPT‑5-Codex work independently for more than 7 hours at a time", OpenAI staffers detailed in a blog post today. GPT-5-Codex spots mistakes it makes during long coding sessions and fixes them automatically. According to OpenAI, the model's ability to tackle time-consuming tasks makes it particularly useful for refactoring. That's the process of changing an application's code base not for the purpose of adding features but rather to improve its quality. Developers might, for example, wish to reduce a code snippet's memory usage or boost response times. OpenAI evaluated GPT-5-Codex's capabilities using an internally-developed refactoring benchmark. The model scored 51.3%, outperforming GPT by more than 17%. GPT-5-Codex can adjust the amount of time it spends on task based on its difficulty. As a result, the model processes simple requests significantly faster than GPT-5. "That means Codex will feel snappier on small, well-defined requests or while you are chatting with it," the OpenA staffers wrote. The ChatGPT developer had employees send coding requests to GPT-5-Codex and ranked those requests based on their model-generated token counts, a measure of hardware usage. According to OpenAI, the bottom 10% used 93.7% fewer tokens than GPT‑5. The most complicated coding prompts, in contrast, cause GPT-5-Codex to spend significantly more time reasoning than GPT-5. OpenAI says the model also brings usability improvements. If developers wish to have GPT-5 generate code that follows a particular style or best practice, they must often enter detailed natural language instructions. GPT-5-Codex reduces the need for pointers. Codex, the AI coding tool through which the model is accessible, was until now available in two editions. One is embedded in ChatGPT and the other is a command line tool. In conjunction with the release of GPT-5-Codex, OpenAI is rolling out a third version that developers can integrate directly into their code editors. The new Codex edition often requires shorter prompts than the other two. According to OpenAI, the reason is that it has access not only to a prompt's contents but also the files open in a developer's code editor. The command line version of Codex, meanwhile, now allows developers to upload explanatory images such as user interface sketches. GPT-5-Codex is immediately available through Codex in ChatGPT's Plus, Pro, Business, Edu and Enterprise plans. OpenAI plans to add the model to its application programming interface in the near future.

OpenAI Introduces GPT-5-Codex, an AI Model Built Just for Coding

OpenAI has announced its newest model, GPT-5-Codex. The new model has been optimized for agentic coding in OpenAI's suite of AI-powered software engineering tools, which is called Codex. This year, AI programs that can write and edit software have emerged as the most lucrative use case for AI, propelling multiple companies to huge revenue increases. These tools are being used both by professional developers to make their work more efficient, and by casual vibe coders, who lack the technical skill to create websites and apps. The Sam Altman-led company claims that by training this new AI model on real-world engineering tasks, it can outperform the default model. In a benchmark that compared that model and GPT-5-Codex's ability to refactor code (essentially reorganizing and cleaning up code), GPT-5-Codex scored nearly 20 percent higher than the default model, which is simply called GPT-5. GPT-5-Codex is also said to be a strong independent worker. It can work autonomously on software for long stretches of time. According to a press release, OpenAI has seen the model "work independently for more than seven hours at a time on large, complex tasks, iterating on its implementation, fixing test failures, and ultimately delivering a successful implementation." The new model could also help alleviate one of the most notable pain points of vibe coding: bad code. Many software developers have remarked that much of their time working with AI-assisted code editors is spent cleaning up the AI's code, which isn't always as thoughtfully written as a human expert's would be. But OpenAI says that GPT-5-Codex has been "trained specifically for conducting code reviews and finding critical flaws." In practice, the company says, this means GPT-5-Codex will review an entire codebase to identify flaws and autonomously test apps to find errors. OpenAI says that Codex currently handles "the vast majority" of proposed changes to code being written by OpenAI staffers, "catching hundreds of issues every day -- often before a human review begins." But even with its improved code review abilities, OpenAI still recommends using Codex as an additional reviewer; it says in a press release that it is "not a replacement for human reviews." Unlike the normal version of GPT-5, GPT-5-Codex won't be immediately available via API, and OpenAI recommends only using the model for coding tasks in Codex-supported environments. In addition, Codex is coming to mobile devices for the first time. Previously, in order to access Codex, you'd either need to use ChatGPT on a desktop computer or invoke Codex in an IDE (integrated development environment) like VSCode or Cursor. Now, Codex will be accessible in the ChatGPT iOS app, enabling easier coding on the go. Codex, and GPT-5-Codex, is available across all of ChatGPT's paid tiers, with $20-per-month ChatGPT Plus members getting enough access to "cover a few focused coding sessions each week." Meanwhile, $200-per-month ChatGPT Pro members will get enough to "support a full workweek across multiple projects." Companies that pay for ChatGPT's SMB-focused Business plan can purchase credits to give their developers more access to Codex, while larger companies with ChatGPT's Enterprise plan get a shared credit pool. In OpenAI's press release, engineers and tech leads at companies including Cisco, Duolingo, Ramp, Vanta, and Virgin Atlantic praised Codex's utility, but it remains to be seen if GPT-5-Codex can help OpenAI take market share away from Anthropic, whose similar Claude Code product has proved very popular with professional and casual software developers. The extended deadline for the 2025 Inc. Best in Business Awards is this Friday, September 19, at 11:59 p.m. PT. Apply now.

OpenAI GPT-5 Codex : Agentic Coding Model MCP Tested

What if coding wasn't just a skill but a conversation, one where your AI collaborator anticipates your needs, adapts to your workflow, and executes complex tasks with precision? OpenAI's GPT-5 Codex is reshaping this vision into reality. As one of the most advanced AI-driven coding tools to date, it promises to streamline multi-component processing (MCP) and redefine how developers interact with code. Imagine seamlessly transitioning between AI models or generating intricate video segments without a hitch, GPT-5 Codex claims to make such scenarios not just possible but routine. But does it deliver on this bold promise, or are there cracks in its polished exterior? In this feature, All About AI explore the dynamic task management and seamless API integration that set GPT-5 Codex apart, while also examining its limitations, such as its steep learning curve and rigid subscription model. You'll discover how this tool handles the demands of modern coding workflows, from creative content generation to automation-heavy tasks. Whether you're a developer curious about its potential or a technical lead evaluating its fit for your team, this deep dive will uncover the strengths and challenges of GPT-5 Codex. As we unpack its capabilities, consider this: could this be the AI that finally bridges the gap between human creativity and machine efficiency? One of the most impressive aspects of GPT-5 Codex is its ability to handle transitions between AI models within MCP server setups with remarkable precision. For example, switching from the Omnihuman model to the Cling AI avatar model was executed efficiently, showcasing its capacity for smooth integration. Using the Codex Command Line Interface (CLI), these transitions can be performed effectively by using well-documented APIs and automation tools. Dynamic task handling is another area where GPT-5 Codex excels. The model demonstrated its ability to manage both simple and complex tasks with speed and accuracy. For instance, generating and merging video segments with a newly integrated avatar model was completed without delays, highlighting its adaptability across both creative and technical domains. This capability underscores its potential to streamline workflows in diverse coding environments. GPT-5 Codex offers a range of benefits that make it a valuable tool for developers and technical teams. Its key strengths include: These features make GPT-5 Codex a reliable and versatile tool for managing a wide array of coding tasks, from automation to creative content generation. Enhance your knowledge on GPT-5 Codex by exploring a selection of articles and guides on the subject. Despite its many strengths, GPT-5 Codex has certain limitations that could impact its usability for some users. One notable challenge lies in the design of the Codex CLI. While powerful, it lacks the intuitive interface of tools like Cloud Code, which may present a learning curve for users accustomed to more user-friendly platforms. Another area requiring attention is the model's high-performance settings. While these settings offer significant potential, their impact on complex workflows remains insufficiently documented. This lack of clarity can hinder users seeking to fine-tune performance for specific tasks or environments. Additionally, the subscription model could benefit from greater flexibility. Users who frequently switch between tools or require access to emerging models, such as Gemini Ultra, may find the current pricing structure restrictive. Offering more adaptable subscription options would make Codex accessible to a broader audience and better accommodate diverse user needs. To fully realize the potential of GPT-5 Codex, further exploration of its advanced features and settings is essential. Conducting comparative analyses with alternative tools, such as Gemini Ultra or other emerging AI models, could provide valuable insights into its relative strengths in areas like speed, accuracy, and usability. By focusing on optimizing performance rather than adhering to specific brands, you can ensure your workflows remain efficient and adaptable to evolving technological advancements. Moreover, addressing user feedback on the CLI design and subscription flexibility could significantly enhance the overall user experience. These improvements would not only make Codex more accessible but also solidify its position as a leading tool in AI-driven coding solutions. GPT-5 Codex offers a robust and versatile solution for modern coding workflows, excelling in dynamic task handling, seamless model integration, and efficient token management. While challenges such as CLI usability and subscription flexibility remain, these do not detract from its overall capabilities. By continuing to refine its features and addressing user needs, you can harness the full potential of this advanced AI tool, making sure your workflows remain efficient, adaptable, and prepared for future innovations in AI-powered coding solutions.

OpenAI GPT-5 Codex Tested : Capabilities, Limitations and Real-World Performance

How good is GPT-5 Codex, really? Imagine a tool so advanced it can generate functional code for complex applications in mere minutes, yet intuitive enough to seamlessly integrate into your existing development workflow. Bold claims like these have surrounded the latest iteration of OpenAI's Codex, sparking both excitement and skepticism in the developer community. Is it truly the fantastic leap forward it promises to be, or does it fall short in critical areas? By examining its performance in real-world scenarios, like building a local real-time transcription app, we can begin to unravel whether GPT-5 Codex is a fantastic option or just another incremental upgrade. In this overview, we'll explore its capabilities, limitations, and the broader implications for developers navigating the evolving landscape of AI-assisted coding. Through the lens of a practical project, Prompt Engineering tests how GPT-5 Codex handles intricate coding tasks, integrates with modern tools like VS Code, and accelerates development timelines. Readers will gain insights into its strengths, such as its ability to tackle complex problem-solving, as well as its weaknesses, like dependency conflicts and limited offline functionality. Beyond the technical details, this discussion also touches on the emotional and professional impact of such a tool, how it could redefine productivity and creativity for developers. Whether you're a seasoned programmer or simply curious about the future of AI in software development, this evaluation offers a nuanced look at what GPT-5 Codex brings to the table, and what it still has to prove. The primary objective of the project was to develop a local transcription app capable of converting audio into text in real-time. To achieve this, the team used the Whisper Small MLX model for transcription, chosen for its balance of speed and accuracy. The app's backend was built using Python and optimized for Apple Silicon (M2 Max), making sure the computational power required for seamless performance. The app was designed with several key features to enhance usability and functionality: These features were carefully crafted to deliver a smooth user experience while maintaining the app's technical reliability. The combination of advanced transcription capabilities and user-friendly design underscored the app's potential as a practical tool for various use cases. The development process was streamlined through the use of modern tools and technologies, which worked cohesively to enhance efficiency and productivity. Key components of the workflow included: This combination of tools enabled the team to build a robust transcription solution in a remarkably short timeframe. The seamless integration of GPT-5 Codex with these technologies highlighted its ability to complement existing development workflows and accelerate project timelines. Here are additional guides from our expansive article library that you may find useful on GPT-5 Codex. While the transcription app's initial setup and implementation were completed in just 20 minutes, the development process was not without challenges. Several obstacles emerged, requiring careful attention and problem-solving: Despite these hurdles, the team successfully addressed the challenges through iterative debugging and developer oversight. For instance, fine-tuning the hotkey functionality ensured consistent performance, while enhancements to the session statistics display improved the app's real-time feedback. These refinements demonstrated GPT-5 Codex's adaptability in generating and optimizing code to meet specific user needs. GPT-5 Codex demonstrated strong performance across several key areas during the development process: However, certain limitations were also observed. The reliance on external dependencies occasionally introduced challenges, such as versioning conflicts, while the inability to access online documentation hindered progress in specific scenarios. Addressing these issues in future iterations of Codex could further enhance its usability and versatility for developers. Looking ahead, the development team has outlined several upgrades to improve the transcription app's functionality and accessibility: These enhancements are designed to expand the app's capabilities and usability, positioning it as a comprehensive solution for real-time transcription needs. By addressing current limitations and incorporating advanced features, the app has the potential to set a new standard in transcription technology. The success of GPT-5 Codex in this project highlights its potential as a fantastic tool for developers. Its strengths in handling complex coding tasks, integrating seamlessly with modern tools, and delivering functional solutions efficiently make it a valuable resource for software development. While challenges such as dependency management and limited access to documentation remain, these issues can be mitigated through iterative improvements and updates. As artificial intelligence and machine learning technologies continue to advance, tools like GPT-5 Codex are poised to play an increasingly central role in shaping the future of software development. By addressing its current limitations and expanding its capabilities, Codex could become an indispensable asset for developers worldwide, allowing them to tackle complex projects with greater speed and precision.

OpenAI Just Dropped A New GPT-5 Codex AI Coding Model for Developers

What if writing code could feel less like solving a puzzle in the dark and more like having a seasoned mentor at your side? OpenAI's latest innovation, the GPT-5 Codex, promises to do just that. Touted as a fantastic option for developers, this advanced AI model doesn't just assist with coding, it redefines the entire process. From streamlining code reviews to tackling sprawling legacy systems, GPT-5 Codex offers a level of precision and adaptability that feels almost human. But here's the kicker: it's not just about saving time. It's about transforming how developers think, create, and solve problems in an era where efficiency and innovation are non-negotiable. In this breakdown, Prompt Engineering explains how how OpenAI's latest updates to its GPT-5 Codex are setting a new standard for AI-assisted development. You'll uncover its dynamic reasoning capabilities, which allow it to tailor its support to the complexity of your task, and its seamless integration with tools like Visual Studio Code and cloud-based platforms. Whether you're curious about its enhanced code review features or its ability to modernize legacy systems, this is more than just a tool, it's a glimpse into the future of software development. So, what does it mean for you and your workflow? Let's unpack the possibilities. GPT-5 Codex is carefully engineered to tackle the real-world challenges faced by developers. Whether you are working on modernizing legacy systems, analyzing intricate codebases, or managing extended projects, this model is designed to optimize your workflow. Its advanced reasoning capabilities allow it to adapt to tasks of varying complexity, making sure efficient resource allocation. For example, when working with a large codebase, GPT-5 Codex can identify dependencies, validate functionality through automated testing, and provide actionable insights to improve code quality. By addressing these critical pain points, the model enables developers to focus on innovation rather than repetitive or time-consuming tasks. GPT-5 Codex introduces several performance enhancements that set it apart from its predecessors. These improvements are designed to deliver tangible benefits to developers: These advancements translate into a more streamlined development process, allowing you to address critical issues effectively without being overwhelmed by irrelevant or inaccurate suggestions. Expand your understanding of ChatGPT 5 with additional resources from our extensive library of articles. One of the standout features of GPT-5 Codex is its dynamic reasoning capability. This functionality enables the model to intelligently adjust its processing effort based on the complexity of the task at hand. For simpler coding problems, it conserves resources by minimizing token usage, making sure quick and efficient responses. On the other hand, for more intricate challenges, it generates detailed and comprehensive solutions, providing the depth of analysis required for complex systems. This adaptability ensures that developers receive the appropriate level of support, whether debugging a straightforward script or architecting a sophisticated application. GPT-5 Codex is designed to integrate effortlessly into your preferred development environment, offering flexibility and convenience. It supports popular IDEs such as Visual Studio Code and Cursor, allowing developers to use its capabilities directly within their coding workspace. For those who prefer command-line tools, the Codex CLI provides a streamlined and efficient interface tailored to their needs. Additionally, the model is accessible through ChatGPT's cloud-based platform, allowing users to switch seamlessly between local and cloud environments. This versatility ensures that GPT-5 Codex can adapt to a wide range of workflows and preferences. The ability to conduct thorough and insightful code reviews is one of GPT-5 Codex's most impactful features. The model is capable of navigating complex codebases, identifying dependencies, and validating correctness through automated testing. By prioritizing critical issues and offering actionable feedback, it significantly reduces the likelihood of errors making their way into production. This not only saves valuable time but also enhances the overall quality and reliability of your software. Developers can rely on GPT-5 Codex to streamline the review process, making sure that their code meets the highest standards. Security remains a top priority for GPT-5 Codex. The model operates within a secure sandbox environment with network access disabled, making sure that no malicious or destructive actions can occur. This feature is particularly valuable for organizations concerned about data security and compliance. By providing a controlled environment, GPT-5 Codex allows developers to use the model confidently, knowing that sensitive information is protected. This robust security framework makes it an ideal choice for businesses handling critical or confidential data. OpenAI offers GPT-5 Codex through a variety of subscription plans, including Plus, Pro, Business, Education, and Enterprise tiers. These plans are designed to cater to a diverse range of users, providing generous rate limits and flexible pricing options. Additionally, OpenAI has announced plans to release an API for Codex CLI, further expanding its integration capabilities. This ensures that developers can access the model in a way that best suits their needs, whether through direct integration into their tools or via standalone applications. The user experience with GPT-5 Codex is tailored to meet the unique needs of different platforms. The Codex CLI offers a direct and optimized interface, ideal for developers seeking a streamlined workflow. Integration with IDEs provides powerful functionality, though performance may vary depending on the specific setup. Regardless of the platform, GPT-5 Codex is designed to simplify complex coding tasks, enhance productivity, and support developers in achieving their goals more efficiently. OpenAI's GPT-5 Codex sets a new benchmark for AI-assisted software development. With its dynamic reasoning capabilities, enhanced code review features, and seamless integration across platforms, it redefines how developers approach their work. Whether you are refactoring legacy systems, conducting in-depth reviews, or managing long-term projects, GPT-5 Codex provides the tools and insights needed to work smarter and more effectively. By addressing the challenges of modern software development, it enables developers to focus on innovation and deliver high-quality solutions with confidence.

OpenAI releases GPT-5-Codex for enhanced software engineering By Investing.com

Investing.com -- OpenAI launched GPT-5-Codex on Monday, a specialized version of GPT-5 optimized for agentic coding in Codex with enhanced capabilities for software engineering tasks. The new model excels at both quick interactive sessions and independently handling complex, lengthy tasks. It also features code review functionality designed to identify critical bugs before software deployment. GPT-5-Codex is now available across all Codex platforms, serving as the default option for cloud tasks and code review. Developers can also select it for local tasks through Codex CLI and the IDE extension. OpenAI has been steadily enhancing Codex since launching Codex CLI in April and Codex web in May. Two weeks ago, the company unified Codex into a single product experience linked to users' ChatGPT accounts, allowing seamless work transitions between local environments and cloud platforms without losing context. The platform now functions across multiple development environments including terminals, IDEs, web browsers, GitHub, and the ChatGPT iOS app. Codex is included with ChatGPT Plus, Pro, Business, Edu, and Enterprise subscription plans. According to OpenAI, these updates advance their vision of creating a coding teammate that understands user context, works collaboratively, and reliably handles team tasks. This article was generated with the support of AI and reviewed by an editor. For more information see our T&C.

New OpenAI GPT-5 Codex Model Released : First Impressions

What if your coding assistant didn't just follow instructions but anticipated your needs, optimized your workflow, and even tackled complex problems with minimal oversight? OpenAI's GPT-5 Codex promises to do just that, raising the bar for AI-driven software development tools. With its ability to dynamically adjust reasoning time, deliver concise code reviews, and integrate seamlessly into existing environments, this latest iteration is more than just an upgrade, it's a potential fantastic option for developers. But does it live up to the hype, or are there trade-offs lurking beneath its polished surface? In this overview, Matt Maher explore the standout features that make GPT-5 Codex a bold step forward, from its agentic programming capabilities to its resource-efficient design. You'll discover how it handles everything from routine automation to intricate problem-solving, and why its performance on benchmarks like Swebench is turning heads. Whether you're curious about its practical applications or wondering if it's ready to tackle your most demanding workflows, this deep dive will offer insights into what sets GPT-5 Codex apart, and where it might still fall short. Sometimes, the real story lies in the details. GPT-5 Codex is purpose-built for software engineering, with a strong emphasis on agentic programming. This feature enables the model to autonomously manage tasks, significantly reducing the need for constant oversight. A key innovation lies in its ability to dynamically adjust reasoning time based on the complexity of the task at hand. The model also excels in industry-standard benchmarks such as Swebench and demonstrates exceptional performance in code refactoring tasks. These capabilities make GPT-5 Codex a versatile tool for developers seeking both speed and reliability in their workflows. Efficiency is a cornerstone of GPT-5 Codex's design, making sure that developers can focus on critical aspects of their projects without unnecessary distractions. The model optimizes token usage by scaling its output according to task complexity: This balance between precision and resource management ensures that developers can achieve their goals without being bogged down by inefficiencies or excessive computational overhead. Expand your understanding of GPT-5 Codex with additional resources from our extensive library of articles. One of the standout features of GPT-5 Codex is its ability to transform the code review process. The model delivers concise and actionable feedback, avoiding overly verbose or redundant comments. This streamlined approach allows developers to quickly identify and address critical issues, significantly reducing the time spent on reviews. By focusing on clarity and relevance, GPT-5 Codex ensures that code reviews are both efficient and effective, allowing teams to maintain high-quality standards without unnecessary delays. GPT-5 Codex is designed for both speed and usability, offering faster response times for well-defined tasks while maintaining the ability to handle complex problems over extended periods. Its outputs are succinct and actionable, allowing developers to implement solutions with minimal back-and-forth. In real-world scenarios, the model has demonstrated its value by resolving coding issues with minimal user intervention. For example, it can identify and fix missing Firestore indexes, providing clear and actionable steps for implementation. Its adaptability to user-defined contexts further enhances its utility, allowing developers to tailor its responses to their specific needs and workflows. The user experience with GPT-5 Codex is designed to be seamless and intuitive. The model integrates effortlessly with tools such as terminal environments and IDE plugins, allowing developers to incorporate it into their existing workflows without disruption. From identifying problems to implementing solutions, GPT-5 Codex ensures a smooth and efficient coding process. Its conversational interface further enhances usability, making it easier for developers to interact with the model and extract meaningful insights. GPT-5 Codex represents a significant advancement in AI-driven coding assistance, but it is not without limitations. Certain tasks may still require iterative refinement to achieve optimal results. However, the model's improvements in efficiency, usability, and adaptability far outweigh these minor drawbacks. Its ability to handle a wide range of tasks with precision and speed makes it an invaluable asset for developers navigating the complexities of modern software engineering. GPT-5 Codex is a powerful tool that redefines the role of AI in software engineering. By focusing on efficiency, adaptability, and user-centric design, it enables developers to work smarter and faster. From automating routine tasks to solving intricate problems, GPT-5 Codex provides a robust solution for the challenges of modern software development. Its seamless integration into existing workflows and its ability to deliver actionable insights make it a fantastic addition to any developer's toolkit.

OpenAI's Agent Codex gets GPT-5: Key improvements explained

From IDEs to GitHub, GPT-5 Codex redefines AI-assisted developer workflows Artificial intelligence is rapidly reshaping the way developers write, test, and review code. OpenAI has now taken a major step forward by upgrading Codex - the model powering its AI coding assistant - with a specialized new version of GPT-5. The rollout of GPT-5-Codex promises smarter, more reliable, and more flexible coding assistance, while also raising questions about how AI might soon become an indispensable part of every developer's toolkit. Also read: What is VaultGemma: World's most privacy conscious AI LLM explained When OpenAI first released Codex in 2021, it was built on GPT-3 and quickly became the foundation of GitHub Copilot. While the tool impressed many with its ability to autocomplete code, it was also infamous for generating incorrect or inefficient snippets. The new GPT-5-Codex builds on lessons from years of developer feedback and significant advances in AI architecture. Instead of being just a "code autocomplete" model, it is now positioned as a full-fledged agent, capable of reasoning about a problem, reviewing code, and even refactoring large repositories. One of the most striking upgrades is what OpenAI calls dynamic "thinking time." Unlike earlier models, which were constrained to a fixed amount of compute per task, GPT-5-Codex can decide on the fly how long to spend solving a problem. If it encounters a simple bug, it may resolve it within seconds. But if it faces a complex code refactoring challenge, it can continue reasoning for hours, sometimes up to seven, before producing an answer. This flexible approach mirrors how human developers work: deciding whether a task requires a quick patch or a deeper, more time-consuming analysis. It also sets GPT-5-Codex apart from other AI coding assistants, which typically stop processing once they hit a pre-determined compute limit. Performance benchmarks show significant gains. On SWE-bench Verified, a standard test for "agentic coding abilities," GPT-5-Codex outperforms the base GPT-5. It also demonstrates better results in code refactoring tasks drawn from established open-source repositories. This matters because refactoring requires not just generating new code, but understanding and preserving existing logic, something past models often struggled with. Beyond benchmarks, OpenAI also enlisted experienced software engineers to evaluate GPT-5-Codex's review comments. The findings: it produces fewer incorrect suggestions and more high-impact insights compared to older versions. For developers, this means less noise and more actionable feedback during code reviews. OpenAI is rolling out GPT-5-Codex broadly across its platforms. It's now available in ChatGPT for Plus, Pro, Business, Education, and Enterprise users. Developers can also access it through the terminal, IDE integrations, or directly within GitHub. API support is on the roadmap, though OpenAI has not yet confirmed a release timeline. Also read: AI will make invisible submarines visible in deep sea: Here's how This distribution strategy highlights OpenAI's intent to make GPT-5-Codex not just a research upgrade but a production-ready coding assistant. With rivals like Anthropic's Claude Code, Anysphere's Cursor, and GitHub Copilot pushing their own AI coding agents, OpenAI is under pressure to prove its edge in real-world developer workflows. Despite its promise, GPT-5-Codex also raises challenges. Dynamic compute allocation, where tasks can run for hours, will inevitably raise questions around latency, cost, and efficiency. Enterprises may hesitate if pricing scales unpredictably with compute usage. There's also the issue of trust: while GPT-5-Codex reduces incorrect suggestions, no AI code model is error-free, and human oversight remains essential for production software. Still, the upgrade represents a major leap forward. If GPT-3 Codex was an autocomplete tool and GPT-4 refined its accuracy, GPT-5-Codex seems poised to act as a true AI development partner - one that not only helps write code but understands, critiques, and reshapes it.