Claude

Select the model to use between Claude, GPT, Gemini, Kimi, Grok or Sonar

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Let’s tell you how you can choose the artificial intelligence model What are you going to use with? Perplexity in a prompt. This is a chatbot known for allowing you to access many cutting-edge models from third-party companies, something it does automatically depending on the request you make. However, if you are going to use Perplexity, it is advisable to know one of its functions basic, being able to choose by hand which model you want to use. And yes, every time Google, Anthropic or OpenAI launch a new model of artificial intelligenceat Perplexity they are going to add it to their catalog. The results will not be exactly the same as if you use the paid versions of ChatGPT, Grok, Claude or Gemini, because Perplexity may modify them a little. However, you will be able to take advantage of the reasoning power of these models. Choose the AI ​​model to use in Perplexity To choose the AI ​​you want to use in Perplexity, you have to look at the box where you write the prompt. In it, you must click on the option AI modelwhich will appear with the icon of what appears to be a chip. It is to the far left of the series of icons that appear at the bottom right in the prompt writing field. When you click on that button, it will appear a list of all models of artificial intelligence that you can use. Both the best and the latest available from Gemini, GPT, Claude, Grok, Kimi or Perplexity’s own Sonar will appear. This is something that you can do in its web version or in its mobile or computer applications. Here, you should know that you can choose the model with each prompt within a conversation with Perplexity. Come on, you can ask a question with one model, and then ask the next question with another. Also, below the list you will see the number of queries you can make with the most modern models. In Xataka Basics | The best prompts to save hours of work and do your tasks with ChatGPT, Gemini, Copilot or other artificial intelligence

Anthropic just accused DeepSeek and other Chinese companies of “distilling” Claude

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For months we have talked about the race between the United States and China to dominate artificial intelligence as if it were only a question of who trains the most powerful model or launches the next version first. But the pulse begins to move to another, more delicate area: that of the rules of the game. When one laboratory accuses another of extracting capabilities from its system to accelerate its own development, the discussion goes beyond the technical. That’s exactly what Anthropic just did by denounce “distillation” campaigns against his model Claude. The complaint. In a text published this Monday, the company claims to have detected “industrial-scale campaigns” aimed at extracting Claude’s capabilities. According to their version, the activities attributed to DeepSeekMoonshot and MiniMax reportedly involved more than 16 million queries, question and answer interactions, and were channeled through approximately 24,000 fraudulent accounts, in violation of their terms of service and regional access restrictions. The race and the suspicion. The announcement by the firm led by Darío Amodei occurs in a context of growing tension around the progress of Chinese AI. Let us remember that DeepSeek altered the Silicon Valley landscape a year ago with the launch of R1, a competitive model that was presented as Developed at a fraction of the cost of American alternatives. The impact was immediate on the markets and revived the political debate in Washington about the technological advantage over China. Distilling is not always cheating. Anthropic itself recognizes that distillation is a common technique in the sector. It consists, in simple terms, of training a less capable model using the responses generated by a more powerful one, something that large laboratories use to create smaller, cheaper versions of their own systems. The problem, according to the company, appears when this practice is used to “acquire powerful capabilities from other laboratories in a fraction of the time and at a fraction of the cost” that developing them independently would entail. In that case, distillation would cease to be an internal optimization and would become, always according to Anthropic, a way of taking advantage of the work of others. Recognizable pattern. The three laboratories would have used fraudulent accounts and proxy services to access Claude on a large scale while trying to avoid detection systems. The company details infrastructures, what it calls “hydra cluster”, extensive networks of accounts that distribute traffic between its API and third-party cloud platforms, so that when one account was blocked, another took its place. Anthropic maintains that what differentiated these activities from normal use was not an isolated query, but rather the massive and coordinated repetition of requests aimed at extracting very specific capabilities from the model. Three campaigns. Although Anthropic presents the campaigns as part of the same dynamic, it distinguishes relevant nuances. DeepSeek would have focused its more than 150,000 queries on extracting reasoning capabilities and generating safe alternatives to politically sensitive questions. Moonshot, with more than 3.4 million queries, would have been oriented towards the development of agents capable of using tools and manipulating computing environments. MiniMax would concentrate the largest volume, more than 13 million queries, and according to Anthropic’s account, it reacted in a matter of hours to the launch of a new system, redirecting its traffic to try to extract capabilities from its most recent system. A geopolitical issue. The company states that illicitly distilled models may lose safeguards that seek to prevent state or non-state actors from using AI for purposes such as the development of biological weapons or disinformation campaigns. It also argues that distillation undermines export controls by allowing foreign laboratories to close the gap in other ways, while at the same time recognizing that executing these large-scale extractions requires access to advanced chips, thus reinforcing the logic of restricting their availability while, at the same time, remembering that the risk would grow if these capabilities end up being integrated into military, intelligence or surveillance systems. Images | Xataka with Nano Banana Pro In Xataka | Seedance is the greatest brutality we have seen generating video. And it has an uncomfortable message: it has surpassed Sora and Veo without NVIDIA chips

The great revolution of GPT-5.3 Codex and Claude Opus 4.6 is not that they are smarter. It’s that they can improve themselves

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Last week, OpenAI and Anthropic simultaneously launched their new AI models specialized in programming: GPT-5.3 Codex and Claude Opus 4.6. Beyond the improvements they represent in performance or speed, which are truly amazing, both companies also stated something that completely changes the rules of the game: AI models are actively participating in their own development. Or put another way: AI is improving itself. Why does this change matter?. Generative artificial intelligence tools are reaching a high level of efficiency and precision, becoming in a few years from being co-workers for simple and specific tasks to being able to be involved in a good part of a development. According to the technical documentation of OpenAI, GPT-5.3 Codex “was instrumental in its own creation,” being used to debug its training, manage its deployment, and diagnose evaluation results. On the other hand, it is worth highlighting the words of Dario Amodei, CEO of Anthropic, who in his personal blog affirms that AI writes “much of the code” in his company and that the feedback loop between the current generation and the next “gains momentum month by month.” In detail. What this means in practice is that each new generation of AI helps build the next, more capable one, which in turn will build an even better version. Researchers call it the “intelligence explosion,” and those developing these systems believe the process has already begun. Amodei has declared publicly that we could be “just 1 or 2 years away from a point where the current generation of AI autonomously builds the next.” Most people use free language models that are available to everyone and are moderately capable of certain tasks. But they are also very limited, and are not a good reflection of what a cutting-edge AI model is capable of today. In a brief session with 5.3-Codex I was able to draw this same conclusion, since the AI ​​tools that big technology companies use in their development are nothing like the most commercial ones that we have freely available in terms of capabilities. The code-first approach. Initial specialization in programming makes more sense than we think. And the idea of ​​companies like OpenAI, Anthropic or Google that their systems were exceptional by writing code before anything else is linked to the fact that developing AI requires enormous amounts of code. And if AI can write that code, it can help build its own evolution. “Making AI great at programming was the strategy that unlocked everything else. That’s why they did it first,” Matt Shumer, CEO of OthersideAI, said in a publication that has given us something to talk about these days on social networks. Between the lines. The new models don’t just write code: they make decisions, iterate on their own work, test applications as a human developer would, and refine the result until they are satisfied. “I tell the AI ​​what I want to build. It writes tens of thousands of lines of code. Then it opens the app, clicks the buttons, tests the features. If it doesn’t like something, it goes back and changes it on its own. Only when it decides it meets its own standards does it come back to me,” counted Shumer describing his experience with GPT-5.3 Codex. What changes with self-reference. Until now, each improvement depended on human teams spending months training models, adjusting parameters and correcting errors. Now, some of that work is performed by AI itself, accelerating development cycles. Just like share Shumer and referring to METR dataan organization that measures the ability of these systems to complete complex tasks autonomously, the time that an AI can work without human intervention doubles approximately every seven months, and there are already recent indications that that period could be reduced to four. And now what. If this trend continues, by 2027 we could see systems capable of working autonomously for weeks on entire projects. Amodei has spoken of models “substantially smarter than almost all humans in almost all tasks” by 2026 or 2027. These are not distant predictions, since the technical infrastructure for AI to contribute to its own improvement is already operational. And these capabilities are what are really turning the technology industry on its head. Cover image | OpenAI and Anthropic In Xataka | We have a problem with AI. Those who were most enthusiastic at the beginning are starting to get tired of it.

What is Claude Cowork, how it works, and what things you can do with this AI assistant on your computer

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Let’s explain to you What is Claude Cowork and how does it work?one of the advanced tools of the artificial intelligence of Claude. It is an automation assistant for the computer, a kind of AI agent which you can ask to do tasks on your PC without you having to touch anything. Let’s start by explaining what it is so that you understand the concept. Then we will tell you how it works, to finish by giving you some examples of the things you can do with it. What is Claude Cowork Claude Cowork is basically a personal assistant with artificial intelligence Designed to work natively on your computer. This way, you can use Claude on your Windows or Mac PC to ask it to do things automatically. It has been designed above all to help you with the repetitive tasks you do in your daily life with files, folders and applications. Imagine being able to ask the AI ​​to do things like rename files in a folder, look for duplicates, or even give you summaries of the contents of these files. It is something similar to an AI Agent, but it is not exactly this. AI agents are capable of doing complex tasks for you, like booking a hotel. However, Claude Cowork is designed specifically for automate tasks with files and applicationsand manage the operating system of your local computer. So it doesn’t have as many features, but it does what it’s trained to do better. This tool is available in the Claude desktop appalthough only for paying users. This means that you always have it available. In addition to this, You can also give access to your browser to be able to ask it to do tasks on it or interact with web content, but for that you need to install the extension Claude in Chrome. How Claude Cowork works The way Claude Cowork works is very simple. You open the Claude application and go to the Cowork tab, and in there you ask him what you want him to do using natural language. When making the request, you will have to specify what you want, the folder where you want it done, and all the details you want. Here, you should think that you are asking a person for the task. If you want to change the name of the files in a folder, you will have to specify that you want to rename them, indicate what folder it is, and even the format, in case you want it to be “Year-Month-Name” or any other. Cowork has controlled access to your file systemso that you can decide and customize which elements you can touch and which ones you can’t. When you make a request you can even choose the folder where you want it to act. This tool will first process your text to understand what you want, and then will chain several actions to carry it out. It will be Claude’s own AI that will figure out the way he wants to do it, and if necessary because it doesn’t work, rectify it to do it another way. In the Claude app, within the Cowork section, you will be able to see step by step what it is doing this assistant. The AI ​​will ask you for permission on each piece of data, for example to rename files or connect to a tool, and you can always see the progress and stop it whenever you want. Lastly, you should know that you can use the connectors and extensions to link web services and applications on your computer and be able to do things in them. You can add your notes application, Spotify, or the messaging app among many others. But also web services such as Gmail, Google Drive, Notion, Trivago, WordPress, and many others. What you can do with Cowork The uses of this tool depend on many things, although there are a series of basic actions that you can know and that will save you a lot of time. They are the following: File management: Manage files in any folder, organizing downloads, renaming batches of files with specific patterns, moving documents between folders, finding and deleting duplicates, zipping and unzipping files, and more. Document processing: You can process various document types by extracting text from PDFs, converting files from one format to another, combining multiple documents into one, or extracting specific data from multiple files to create summaries. Automation of repetitive tasks: It can also help you automate tasks you do every day or week, such as preparing reports by putting together data from different files, creating folder structures for new projects, or making organized backups of certain files. Cleaning and maintenance: You can also ask it to do tasks like asking it to delete old files that you no longer need, clean up temporary folders, organize your photo or music library, or find large files that are taking up space. But these are just the basic features of Cowork, and you can get it to do many more things connecting it to cloud services, other applications, or installing the extension to use Chrome. To give an example, I have asked you to create a text file with the list of all the songs (more than 600) that I have in a certain playlist on my Spotify account. So Claude ran his Chrome extension, I could see it go to my Spotify account, I gave him permission to log in, he then looked for various ways to read the songs in the list (first a script and then using the mouse to scroll), and then he created the plain text document. In Xataka Basics | Claude: 23 functions and some tricks to get the most out of this artificial intelligence

What is Claude Code and what this tool can do to program with artificial intelligence from your computer terminal

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Let’s explain to you what is Claude Code or Claude CodeAnthropic’s tool to create code with the artificial intelligence directly into your computer terminal. This will mean that you will not need to install anything or be asking questions without stopping. Claude. We are going to start by explaining to you in a simple way what this tool is and the basics of how it works. Then, we will explain to you what things can you do and what this program for developers is for. What is Claude Code Claude Code or Claude Code is a command line application developed by Anthropic, the same creators of Claude’s AI. This is a program that allows you perform programming tasks from the terminal from your computer without having to use another program. The computer’s terminal is that command screen that you have in Windows called PowerShell, and in macOS and GNU/Linux it is simply the terminal. Instead of installing a common program that you have to open, the program is installed directly in the terminal, and you can use it to do so. With this program, you can use Claude to generate code within the terminal. And it not only generates code snippets, but can also act and reason directly on your projects by linking it to Github. Claude Code can read, analyze and edit content in your codebase. But in addition to this, you can also run tests and correct any errors generatedalso managing workflows. The classic way to generate code with Claude is to enter his app or website, explain what you want, and have the AI ​​create the code for you. Then you have to copy the code, paste it into the code editor you have installed and do the tests, so that if something fails you can go back to Claude, explain the problem, have him generate the corrected code again and repeat the process. Meanwhile, with Claud Code the process changes and is radically simplified. You simply open your terminal, run Claud Code in it, write a prompt or command saying what you want and that’s it. Then this AI will access your files, write code, run it, detect errors, fix them, and try again. It does all this autonomously, although you can supervise the process and intervene whenever you want. What Claude Code can do Claude Code has direct access to your file systemand can execute real commands on the computer. With all this, what this tool can do is the following: Read your files to see the code that you already have created in a folder, and thus understand the context of your project. Create new files complete with code, but also with configurations and documentation. Modify existing files editing the code you have in them to make any type of modifications. Work on an interim basisbeing able to read the error messages that appear if something fails in the code, and starting to correct these errors automatically. All this will save you a lot of time in your programming work, since you will not need to manually create folder structures, configure development tools, configure databases, create interfaces, write code, or anything. Claude will do all this automatically with just You explain the type of application you want to create in a prompt. You can also ask you to add features to existing projects with a command in which you mention the project, debug errors, review code, whatever you need. Therefore, we are faced with a tool for developers which will help you save a lot of time. Although as always happens in artificial intelligence, can make mistakes and have hallucinationsalthough within the world of AI programming Claude is one of the best. In Xataka Basics | Claude: 23 functions and some tricks to get the most out of this artificial intelligence

Creating a C compiler cost 2 million dollars and took 2 years. Claude Opus 4.6 did it in two weeks for $20,000

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We are facing a technological inflection point. Uo in which software engineering, one of the most complex and demanding technical tasks in history, little by little It is becoming the “killer app” of AI. It is clear that generative AI models are not perfect, but we continue to see extraordinary evolution. The latest example? The C compiler that Claude Opus 4.6 programmed all by himself. what has happened. Nicholas Carlini, researcher at Anthropic, I counted yesterday how “I’ve been experimenting with a new way of monitoring language models that we’ve called “agent teams””. What it has done is ensure that several programming agents work in parallel using the recently released Claude Opus 4.6, and thanks to that it has developed something exceptional with 16 of these agents: a C code compiler. Hello CCC. At Anthropic they have called it Claude’s C Compiler (CCC), and they have published the code, completely generated by Opus 4.6, on GitHub. The project consists of 100,000 lines of Rust code that were generated in two weeks with an API cost of $20,000. And it works: with it they have compiled a functional Linux 6.9 kernel on x86, ARM and RISC-V. Before it was (at least) two million dollars and two years. What this experiment has achieved is to demonstrate how software development can be much cheaper and faster thanks to the use of these agents. Although there is no readily available data on how much time and money compilers cost in the past, the size of these products was enormous, as is the case with Microsoft Visual C++For example. It is difficult to know how much it cost, but it is estimated that it involved 15-20 people working for five years. That’s a lot of man hours and a lot of money to develop and polish that compiler. The estimate of two years and two million dollars may in fact be overly optimistic. another example. Historically, building a C compiler from scratch was considered one of the pinnacles of systems engineering. Not only was in-depth knowledge of processor architecture required, but thousands of man-hours were required to manage optimization and machine code generation. In the 90s the company Cygnus Solutions (clue in compiler development gcc) came to invest more than 250 million in a decade to maintain and port build tools. The real cost was not just in the final lines of code, but in countless hours analyzing CPU and memory patterns to make the resulting binary efficient. Far from perfect, but… Carlini himself explained in the post that this compiler had serious limitations and for example “it does not have a 16-bit x86 compiler which is essential to start Linux outside of “real mode”, and it does not have its own assembler nor its linker“. It is probably far from mature compilers, but even so the achievement remains exceptional and points to that future in which even very complex developments can be supported with AI. They will be expensive, no doubt, but their total development will probably be a fraction of what they cost a few years ago. Cursor already demonstrated it. Before Anthropic launched its AI-programmed compiler, Cursor completed a similar project, combining GPT-5.2 agents into its development platform to create a working browser in a week. In total the AI ​​programmed three million (!) lines of code in Rust, and although it was again far from being perfect or competing with Chrome, it demonstrated the current capacity of these agentic programming systems. Turning point (especially for Anthropic). For the SemiAnalysis experts Claude Code, current leading exponent of this new era of AI-driven programming, is a paradigm shift: “We believe that Claude Code is the turning point for AI agents and is a glimpse into the future of how AI will work.” This prestigious newsletter predicts an exceptional 2026 for Anthropic, and so much so that they believe it will “dramatically surpass OpenAI.” You ask, the AI ​​programs. If you have tried the vibe codingI’m sure you agree with me: AI allows you to do things you would never have dreamed of. What I did a few weeks ago with Immich made it clear to me, and I continue experimenting with AI and programming “custom” things that solve real problems and needs for me. Yes, for now they are for me and therefore they are not large and complex systems that need to be put into production as happens in professional environments, but I am clear that this is being done little by little and more will be done. In fact, both OpenAI and Anthropic have stood out how in the development of their latest models part of the work has been done, paradoxically, by those same models, which have fed back to each other. And the result is in production and used by millions of people. Something is changing. And it’s something big. In Xataka | OpenAI has a problem: Anthropic is succeeding right where the most money is at stake

Claude Code is being the big favorite among programmers. So much so that he already signs 4% of everything that is uploaded to GitHub

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It is worth taking a look at how generative AI It is transforming the daily lives of many programmers. And little by little these tools are conquering the environments of millions of developers. The achievement in this aspect is for Claude CodeAnthropic tool, which already represents 4% of all public commits uploaded to GitHub, according to a report by SemiAnalysis. The media says that, if it maintains its current pace of adoption, it is very possible that it will reach 20% of all daily contributions before the end of 2026. Although there are nuances that should be highlighted. Why is it important. Claude Code is slowly gaining the reputation of being the favorite tool for programming with AI. The tool works radically differently than traditional code wizards. It is not a chatbot integrated into an editor like Cursorbut rather a terminal tool that reads entire code bases, schedules multi-step tasks, and executes them with full access to the developer’s computer. You can start from spreadsheets, entire repositories, or web links, understand context, verify details, and complete complex objectives iteratively. The interesting thing is that, by default, Claude Code includes a co-authorship note if the user has used this tool in their program and uploads it to Github. But the user can also decide not to include that signature if modify the parameters by Claude Code, so that 4% could remain small. In March of last year, a month after its launch in private beta, Claude Code already had the co-authorship of about 15,000 Github commits in a period of 48 hours. Things have ended up escalating quickly. Opinions. The newsletter stands out the comments of some industry professionals regarding the vibe codding. Andrej Karpathy, one of the first to coin the term vibe codding, recognized in a post that he is “starting to lose the ability to write code manually.” Ryan Dahl, creator of Node.js, counted directly that “the era of humans writing code is over.” Boris Cherny, creator of Claude Code, assures that “practically 100% of our code is written by Claude Code + Opus 4.5“. Even Linus Torvalds, creator of Linux, has fooled around with vibe codding for some of his personal projects. It should be noted that, despite all the benefits of Claude Code, it is not perfect. Already we pointed out some time ago the words of Kelsey PiperAmerican journalist for The Argument, who explained that 99% of the time using Claude Code is like having a magical, tireless genie, but 1% of the time it’s like yelling at a pet for peeing on the couch. He can and does make mistakes. It also gets stuck. Hence, the expertise of the person who uses it also plays a very important role. Beyond programming. There is an increasingly latent threat with the use of AI tools (well there are a few that accumulate already). And according to account SemiAnalysis, any information work that follows the READ-THINK-WRITE-CHECK pattern can be automated with this technology. The report mentions sectors such as financial services, legal, consulting and data analysis, which add up to billions of workers globally. Anthropic has already taken the next step with coworkreleased a few weeks ago, which is basically Claude Code applied to general office work. According to the company itself, Cowork was developed by four engineers in ten days, mostly with code generated by Claude Code himself. The tool can create spreadsheets from receipts, organize files by content, write reports from scattered notes… And all with access to your computer. The big consultancies and AI. In December, Accenture signed an agreement to train 30,000 professionals on Claude, the largest deployment of Claude Code to date. OpenAI, for its part, Frontier has launched focused on business adoption so as not to lose steam in the field of corporate use of AI, a business that can end up being very lucrative for startups. Cover image | Anthropic and Mohammad Rahmani In Xataka | Programming is the new board of AI. OpenAI and Anthropic have made it clear with GPT-5.3-Codex and Claude Opus 4.6

Programming is the new board of AI. OpenAI and Anthropic have made it clear with GPT-5.3-Codex and Claude Opus 4.6

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When ChatGPT broke out in November 2022, OpenAI seemed unrivaled. And, to a large extent, that was the case. That chatbot, despite its errors and limitations, inaugurated a category of its own. However, in the technology sector advantages are rarely permanent and, in 2026, the position of the company led by Sam Altman It’s a far cry from what it had then. Google has managed to attract the general public with Nano Banana Prowhile Gemini steadily gaining ground as an artificial intelligence chatbot. At the same time, ChatGPT’s market share has fallen significantly in some markets. Anthropic, for its part, has established itself as a reference in software engineering and has become one of the preferred tools among programmers. In this race to set the pace of AI, this Thursday we witnessed a curious movement: the almost simultaneous arrival of two models focused on programming, GPT-5.3-Codex and Claude Opus 4.6. The coincidence does not seem coincidental and reflects the extent to which the major players in the sector compete to define the next step, in a scenario where the main beneficiaries are, once again, the users. With these new models already on the table, the question becomes what they really contribute. There are plenty of promises and they are also beginning to appear benchmarks comparable that help to place them. So, therefore, it is time to look in a little more detail at what OpenAI and Anthropic propose for those who use AI as a development tool. GPT-5.3-Codex and Opus 4.6 enter the scene: what each promises to developers GPT-5.3-Codex is presented as a model focused on scheduling agents which seeks to expand the scope of what a developer can delegate to AI. OpenAI claims that it combines improvements in code performance, reasoning and professional knowledge over previous generations and is 25% faster. With this balance, the system is oriented to prolonged tasks that involve research, use of tools and complex execution, while also maintaining the possibility of intervening and guiding the process in real time without losing the work thread. One of the most striking elements that OpenAI highlights in this generation is the role that Codex itself would have had in its development. The team used early versions of the model to debug training, manage deployment, and analyze test and evaluation results, an approach that accelerated research and engineering cycles. Beyond that internal process, GPT-5.3-Codex also shows progress in practical tasks such as the autonomous creation of web applications and games. The company has published two examples that we can try right now by clicking on the links: a racing game with eight maps and a diving game to explore reefs. Anthropic’s turn comes with Claude Opus 4.6, an update that the company presents as a direct improvement in planning, autonomy and reliability within large code bases. The model, they claim, can sustain agentic tasks for longer, reviewing and debugging its own work more accurately. The idea is that we can use these capabilities in tasks such as financial analysis, documentary research or creating presentations. Added to this is a context window of up to one million tokens in beta phase, a leap that seeks to reduce the loss of information in long processes and reinforce the usefulness of the system. Beyond the core of the model, Anthropic accompanies Opus 4.6 with a series of changes aimed at prolonging its usefulness in real workflows. Among them there are mechanisms such as the so-called “adaptive thinking”, which allows the system automatically adjust the depth of your reasoning depending on the context. Configurable effort levels and context compression techniques designed to sustain long conversations and tasks without exhausting the available limits also appear on the scene. Added to this are teams of agents that can be coordinated in parallel within Claude Code and deeper Excel or PowerPoint integration. While OpenAI’s product, GPT-5.3-Codex, is not yet available in the API, Anthropic’s is. Maintains the base price of $5 per million entry tokens and $25 per million exit tokenswith nuances such as a premium cost when the prompts exceed 200,000 tokens. Measure who wins with numbers? When trying to put GPT-5.3-Codex and Claude Opus 4.6 face to face, the main obstacle is not the lack of figures, but rather their difficult correspondence. Each company selects evaluations that best reflect its progress and, although many belong to similar categories, they differ in methodology, versions or metrics, which prevents a direct reading. In this type of models, this fragmentation of results is part of the state of the technology itself, but also requires cautious interpretation that separates technical demonstrations from truly equivalent comparisons. Only from this filter is it possible to identify the few points where both systems can be measured under comparable conditions and draw useful conclusions for developers. If we restrict the analysis to truly comparable metrics, the common ground between GPT-5.3-Codex and Claude Opus 4.6 is limited to two specific evaluations identified through our own research: Terminal-Bench 2.0 and OS World in its verified version. The results show a distribution of strengths rather than a clear supremacy. GPT-5.3-Codex marks a 77.3% in Terminal-Bench 2.0 compared to 65.4% for Opus 4.6, which points to greater efficiency in terminal-centric workflows. On the contrary, Opus 4.6 reaches a 72.7% on OSWorldsurpassing the 64.7% of GPT-5.3-Codex in general interaction tasks with the system, a contrast that reinforces the idea of ​​specialization according to the environment of use. So we could say that the capabilities described by each manufacturer point to tools that are no longer limited to generating code, but rather seek to participate in prolonged processes of analysis, execution and review within real professional environments. This transition introduces new selection criteria that go beyond punctual performance. In Xataka | OpenAI has a problem: Anthropic is succeeding right where the most money is at stake

Anthropic has rewritten his 25,000-word “Constitution” for Claude. It is the manual for how AI should behave

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Anthropic has published a completely renewed version of the so-called “Claude Constitution”. Yes friends, an AI also needs a constitution, or at least a series of documents that explain with total transparency what direction the company has decided to take with its AI tool. It is a way to save us trouble in the event that become aware. The document The question in question consists of 80 pages and nearly 25,000 words, and basically shows what values ​​Anthropic relies on to train its models and what they hope to achieve with it. Alluding to Asimov, it would be something like a broader and more complex version of his three laws of robotics. Why it is important. Anthropic carries a good time trying to differentiate from OpenAI, Google or xAI, wanting to position itself as the most ethical and safe alternative on the market. This Constitution is the centerpiece of their training method called “Constitutional AI”, where the model itself uses these principles to self-criticize and correct its responses during learning, instead of relying exclusively on human feedback. The document is not written for users or researchers: it is written for Claude. It was time to update. The first version of the Constitution, published in 2023, was a list of principles drawn from sources such as the UN Universal Declaration of Human Rights or, as they mention from Fortune, from Apple’s terms of service. Now, according to Anthropic, they have taken a completely different approach: “To be good actors in the world, AI models like Claude need to understand why we want them to behave in certain ways, rather than simply specifying what we want them to do,” affirms the company in its statement. The new document is structured around four fundamental values, and the most interesting thing is that Claude must prioritize them in this order when they conflict: Be largely secure: Do not undermine human AI oversight mechanisms during this critical phase of development. Be broadly ethical: act honestly, according to good values, avoiding inappropriate, dangerous or harmful actions. Comply with Anthropic guidelines– Follow specific company instructions when relevant. Be genuinely helpful: benefit the operators and users with whom it interacts. The majority of the document is concerned with developing these principles in more detail. In the utility section, Anthropic describe to Claude as “a brilliant friend who also possesses the knowledge of a doctor, lawyer and financial advisor.” But it also sets absolute limits, called “hard constraints,” that Claude must never cross: not provide significant assistance for bioweapon attacks, not create malware that can cause serious harm, not assist in attacks on critical infrastructure such as power grids or financial systems, and not help “kill or incapacitate the vast majority of humanity,” among others. Consciousness. The most striking part of the document appears in the section titled “The Nature of Claude,” where Anthropic openly acknowledges its uncertainty about whether Claude could have “some kind of conscience or moral status.” “We are concerned about Claude’s psychological safety, sense of identity, and well-being, both for Claude’s own sake and because these qualities may influence his integrity, judgment, and safety,” they count from the company. The company claims to have an internal team dedicated to “model well-being” that examines whether advanced systems could be sentient. Amanda Askell, the Anthropic philosopher who led the development of this new Constitution, explained told The Verge that the company doesn’t want to be “completely dismissive” about this issue, because “people wouldn’t take it seriously either if you just said ‘we’re not even open to this, we don’t investigate it, we don’t think about it.’” The document also raises complex moral dilemmas for Claude. For example, it states that “just as a human soldier might refuse to shoot peaceful protesters, or an employee might refuse to violate antitrust law, Claude should refuse to assist with actions that concentrate power in illegitimate ways. This is true even if the request comes from Anthropic itself.” And now what. Anthropic has published the entire Constitution under a Creative Commons CC0 1.0 license, meaning anyone can freely use it without asking permission. The company promises to maintain an updated version on its website, considering it to be a “living document and a continuous work in progress.” Cover image | Andrea De Santis and Anthropic In Xataka | Company CEOs say AI is saving them a day of work a week. Employees say otherwise

Claude has become more than just a rival to OpenAI: he is its new existential threat

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Several software stocks are falling just since Claude Cowork It’s going viral. Those collected by iShares Expanded Tech Software ETFwhich has a cumulative drop of 6.4% in the last five days. It has also been a few days since OpenAI announced that it is going to introduce ads on ChatGPT. Why important. It’s not just that Claude Cowork is cool and works well. The thing is that OpenAI’s business model is beginning to show cracks while Anthropic gains ground where it matters: in companies that really pay. In figures. Claude dominates 54% of the AI ​​programming market. In business environments controls 42%more than double that of OpenAI. This last piece of information is from six months ago, presumably now it has gotten worse. Cowork has only made accelerate the trend. 20% of Anthropic’s revenue comes from Claude Code alone. Meanwhile, ChatGPT quota has gone from 87% to 64% in a year. In Xataka People are holding funerals for retired AI models for a reason: they are not a "tool" but a support The background. According to historical data since 2001 that collect Sherwood Newswhen the software ETF falls at least 5% in a month, the S&P 500 usually also falls between 5% and 6%, but this time it has not been like that: it has risen 1%. The overall market going up while software goes down has only happened 28 times in over twenty years. And three of them have been this week. Between the lines. Doug O’Laughlin of SemiAnalysis explains it this way in Sherwood News: “Claude Code is the ChatGPT moment repeated. You have to try it to understand it.” His argument is devastating for traditional software. Workflows, interfaces, integrations are going to stop mattering. The only valuable thing will be access to the data via API. Everything else is generated instantly. Yes, but. OpenAI urgently needs money to build its data centers. And it does not have an ecosystem of services like Google or Meta to finance itself. Hence the newly announced announcements for ChatGPT, which will arrive “in the coming weeks” as announced on Friday. Clearly it is a way to better monetize the hundreds of millions of free users, and with that cash flow sustain their growth and spending. On the other hand, Claude Code is powerful, but not perfect: as Kelsey Piper said99% of the time using Claude Code is like having a magical, tireless genie, but 1% of the time it’s like yelling at a pet for peeing on the couch. He keeps making mistakes, sometimes gets stuck on complex tasks. {“videoId”:”x9u4ml2″,”autoplay”:false,”title”:”Does Gemini 3 surpass ChatGPT? This is Google’s new AI”, “tag”:”Webedia-prod”, “duration”:”156″} And now what. For software companies, O’Laughlin’s message is devastating: get out of “information work” as soon as possible. If your differentiation is doing things faster or with better design, you’re done. The only thing that will matter is who has the data and who controls access via API. As summarized Axios in his analysis of the weekit’s unclear who wins the AI ​​race. But the pace is accelerating with no signs of slowing down. And what is increasingly clear is who is losing it. In Xataka | The AI ​​of 2026 brings an uncomfortable truth: the most useful will be the one that watches us the most Featured image | Anthropic (function() { window._JS_MODULES = window._JS_MODULES || {}; var headElement = document.getElementsByTagName(‘head’)(0); if (_JS_MODULES.instagram) { var instagramScript = document.createElement(‘script’); instagramScript.src=”https://platform.instagram.com/en_US/embeds.js”; instagramScript.async = true; instagramScript.defer = true; headElement.appendChild(instagramScript); – The news Claude has become more than just a rival to OpenAI: he is its new existential threat was originally published in Xataka by Javier Lacort .

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