There are many good places for advertising. A conversation with Claude is not one of them.

Advertising drives competition, helps people discover new products, and allows services like email and social media to be offered for free. We’ve run our own ad campaigns, and our AI models have, in turn, helped many of our customers in the advertising industry.

But including ads in conversations with Claude would be incompatible with what we want Claude to be: a genuinely helpful assistant for work and for deep thinking.

We want Claude to act unambiguously in our users’ interests. So we’ve made a choice: Claude will remain ad-free. Our users won’t see “sponsored” links adjacent to their conversations with Claude; nor will Claude’s responses be influenced by advertisers or include third-party product placements our users did not ask for.

The nature of AI conversations

When people use search engines or social media, they’ve come to expect a mixture of organic and sponsored content. Filtering signal from noise is part of the interaction.

Conversations with AI assistants are meaningfully different. The format is open-ended; users often share context and reveal more than they would in a search query. This openness is part of what makes conversations with AI valuable, but it’s also what makes them susceptible to influence in ways that other digital products are not.

Our analysis of conversations with Claude (conducted in a way that keeps all data private and anonymous) shows that an appreciable portion involve topics that are sensitive or deeply personal—the kinds of conversations you might have with a trusted advisor. Many other uses involve complex software engineering tasks, deep work, or thinking through difficult problems. The appearance of ads in these contexts would feel incongruous—and, in many cases, inappropriate.

We still have much to learn about the impact of AI models on the people who use them. Early research suggests both benefits—like people finding support they couldn’t access elsewhere—and risks, including the potential for models to reinforce harmful beliefs in vulnerable users. Introducing advertising incentives at this stage would add another level of complexity. Our understanding of how models translate the goals we set them into specific behaviors is still developing; an ad-based system could therefore have unpredictable results.

Incentive structures

Being genuinely helpful is one of the core principles of Claude’s Constitution, the document that describes our vision for Claude’s character and guides how we train the model. An advertising-based business model would introduce incentives that could work against this principle.

Consider a concrete example. A user mentions they’re having trouble sleeping. An assistant without advertising incentives would explore the various potential causes—stress, environment, habits, and so on—based on what might be most insightful to the user. An ad-supported assistant has an additional consideration: whether the conversation presents an opportunity to make a transaction. These objectives may often align—but not always. And, unlike a list of search results, ads that influence a model’s responses may make it difficult to tell whether a given recommendation comes with a commercial motive or not. Users shouldn’t have to second-guess whether an AI is genuinely helping them or subtly steering the conversation towards something monetizable.

Even ads that don’t directly influence an AI model’s responses and instead appear separately within the chat window would compromise what we want Claude to be: a clear space to think and work. Such ads would also introduce an incentive to optimize for engagement—for the amount of time people spend using Claude and how often they return. These metrics aren’t necessarily aligned with being genuinely helpful. The most useful AI interaction might be a short one, or one that resolves the user’s request without prompting further conversation.

We recognize that not all advertising implementations are equivalent. More transparent or opt-in approaches—where users explicitly choose to see sponsored content—might avoid some of the concerns outlined above. But the history of ad-supported products suggests that advertising incentives, once introduced, tend to expand over time as they become integrated into revenue targets and product development, blurring boundaries that were once more clear-cut. We’ve chosen not to introduce these dynamics into Claude.

Our approach

Anthropic is focused on businesses, developers, and helping our users flourish. Our business model is straightforward: we generate revenue through enterprise contracts and paid subscriptions, and we reinvest that revenue into improving Claude for our users. This is a choice with tradeoffs, and we respect that other AI companies might reasonably reach different conclusions.

Expanding access to Claude is central to our public benefit mission, and we want to do it without selling our users’ attention or data to advertisers. To that end, we’ve brought AI tools and training to educators in over 60 countries, begun national AI education pilots with multiple governments, and made Claude available to nonprofits at a significant discount. We continue to invest in our smaller models so that our free offering remains at the frontier of intelligence, and we may consider lower-cost subscription tiers and regional pricing where there is clear demand for it. Should we need to revisit this approach, we’ll be transparent about our reasons for doing so.

Supporting commerce

AI will increasingly interact with commerce, and we look forward to supporting this in ways that help our users. We’re particularly interested in the potential of agentic commerce, where Claude acts on a user’s behalf to handle a purchase or booking end to end. And we’ll continue to build features that enable our users to find, compare, or buy products, connect with businesses, and more—when they choose to do so.

We’re also exploring more ways to make Claude a focused space to be at your most productive. Users can already connect third-party tools they use for work—like Figma, Asana, and Canva—and interact with them directly within Claude. We expect to introduce many more useful integrations and expand this toolkit over time.

All third-party interactions will be grounded in the same overarching design principle: they should be initiated by the user (where the AI is working for them) rather than an advertiser (where the AI is working, at least in part, for someone else). Today, whether someone asks Claude to research running shoes, compare mortgage rates, or recommend a restaurant for a special occasion, Claude’s only incentive is to give a helpful answer. We’d like to preserve that.

A trusted tool for thought

We want our users to trust Claude to help them keep thinking—about their work, their challenges, and their ideas.

Our experience of using the internet has made it easy to assume that advertising on the products we use is inevitable. But open a notebook, pick up a well-crafted tool, or stand in front of a clean chalkboard, and there are no ads in sight.

We think Claude should work the same way.

EXPLORING NEW PLANETS means that you’re always operating in the past. It takes about twenty minutes for a signal to reach a Mars rover from Earth; by the time a new instruction arrives, the rover will already have acted on the previous one.

But on December 8 and 10, 2025, the commands that were sent to NASA’s Perseverance Rover looked like something from the future. That’s because, for the first time ever, they’d been written by an AI.

Specifically, they were written by Anthropic’s AI model, Claude. Engineers at NASA’s Jet Propulsion Laboratory (JPL) used Claude to plot out the route for Perseverance to navigate an approximately four-hundred-meter path through a field of rocks on the Martian surface.

Because of the delay in the signal to the rover, operators can’t micromanage where it drives. They plan a route, send it, and only later see the results. Until now, human experts have always been the ones to do that planning. This time, Claude lent a hand.

Four hundred meters isn’t far: it’s one lap of a running track. But it’s a start. Claude—the same AI model that people use to draft emails, build software apps, and analyze their company’s finances—is now helping humanity explore other worlds.

The Perseverance Rover—a car-sized robot bristling with cameras and scientific equipment—has been active on Mars since it landed in February 2021. Its mission is to characterize the planet’s geology and past climate, collecting samples of Martian rock and regolith (broken rocks and dust) and paving the way for human exploration of the Red Planet. Another of its key objectives is astrobiological in nature: its landing site, the forty-five-kilometer-wide Jezero crater, was chosen because of the evidence that once, billions of years ago, it contained water—water that might have supported microbial life. So far, the rover has discovered tantalizing hints of what might be ancient biology on Mars.

But driving on the Martian surface is hardly trivial. Every rover drive needs to be carefully planned, lest the machine slide, tip, spin its wheels, or get beached. So ever since the rover landed, its human operators have painstakingly laid out waypoints—they call it a “breadcrumb trail”—for it to follow, using a combination of images taken from space and the rover’s onboard cameras. Once it’s drawn up, the plan is transmitted across the 362 million kilometers between Earth and Mars using the Deep Space Network. Having received the signals, the rover embarks on its trip.

This is high-stakes work. In 2009, the Spirit rover, one of the forebears of Perseverance, drove into a sand trap and never moved again.

Claude Sonnet 4.6 is our most capable Sonnet model yet. It’s a full upgrade of the model’s skills across coding, computer use, long-context reasoning, agent planning, knowledge work, and design. Sonnet 4.6 also features a 1M token context window in beta.

For those on our Free and Pro plans, Claude Sonnet 4.6 is now the default model in claude.ai and Claude Cowork. Pricing remains the same as Sonnet 4.5, starting at $3/$15 per million tokens.

Sonnet 4.6 brings much-improved coding skills to more of our users. Improvements in consistency, instruction following, and more have made developers with early access prefer Sonnet 4.6 to its predecessor by a wide margin. They often even prefer it to our smartest model from November 2025, Claude Opus 4.5.

Performance that would have previously required reaching for an Opus-class model—including on real-world, economically valuable office tasks—is now available with Sonnet 4.6. The model also shows a major improvement in computer use skills compared to prior Sonnet models.

As with every new Claude model, we’ve run extensive safety evaluations of Sonnet 4.6, which overall showed it to be as safe as, or safer than, our other recent Claude models. Our safety researchers concluded that Sonnet 4.6 has “a broadly warm, honest, prosocial, and at times funny character, very strong safety behaviors, and no signs of major concerns around high-stakes forms of misalignment.”

Computer use

Almost every organization has software it can’t easily automate: specialized systems and tools built before modern interfaces like APIs existed. To have AI use such software, users would previously have had to build bespoke connectors. But a model that can use a computer the way a person does changes that equation.

In October 2024, we were the first to introduce a general-purpose computer-using model. At the time, we wrote that it was “still experimental—at times cumbersome and error-prone,” but we expected rapid improvement. OSWorld, the standard benchmark for AI computer use, shows how far our models have come. It presents hundreds of tasks across real software (Chrome, LibreOffice, VS Code, and more) running on a simulated computer. There are no special APIs or purpose-built connectors; the model sees the computer and interacts with it in much the same way a person would: clicking a (virtual) mouse and typing on a (virtual) keyboard.

Across sixteen months, our Sonnet models have made steady gains on OSWorld. The improvements can also be seen beyond benchmarks: early Sonnet 4.6 users are seeing human-level capability in tasks like navigating a complex spreadsheet or filling out a multi-step web form, before pulling it all together across multiple browser tabs.

The model certainly still lags behind the most skilled humans at using computers. But the rate of progress is remarkable nonetheless. It means that computer use is much more useful for a range of work tasks—and that substantially more capable models are within reach.

I believe deeply in the existential importance of using AI to defend the United States and other democracies, and to defeat our autocratic adversaries.

Anthropic has therefore worked proactively to deploy our models to the Department of War and the intelligence community. We were the first frontier AI company to deploy our models in the US government’s classified networks, the first to deploy them at the National Laboratories, and the first to provide custom models for national security customers. Claude is extensively deployed across the Department of War and other national security agencies for mission-critical applications, such as intelligence analysis, modeling and simulation, operational planning, cyber operations, and more.

Anthropic has also acted to defend America’s lead in AI, even when it is against the company’s short-term interest. We chose to forgo several hundred million dollars in revenue to cut off the use of Claude by firms linked to the Chinese Communist Party (some of whom have been designated by the Department of War as Chinese Military Companies), shut down CCP-sponsored cyberattacksthat attempted to abuse Claude, and have advocated for strong export controls on chips to ensure a democratic advantage.

Anthropic understands that the Department of War, not private companies, makes military decisions. We have never raised objections to particular military operations nor attempted to limit use of our technology in an ad hoc manner.

However, in a narrow set of cases, we believe AI can undermine, rather than defend, democratic values. Some uses are also simply outside the bounds of what today’s technology can safely and reliably do. Two such use cases have never been included in our contracts with the Department of War, and we believe they should not be included now:

• Mass domestic surveillance. We support the use of AI for lawful foreign intelligence and counterintelligence missions. But using these systems for mass domestic surveillance is incompatible with democratic values. AI-driven mass surveillance presents serious, novel risks to our fundamental liberties. To the extent that such surveillance is currently legal, this is only because the law has not yet caught up with the rapidly growing capabilities of AI. For example, under current law, the government can purchase detailed records of Americans’ movements, web browsing, and associations from public sources without obtaining a warrant, a practice the Intelligence Community has acknowledged raises privacy concerns and that has generated bipartisan opposition in Congress. Powerful AI makes it possible to assemble this scattered, individually innocuous data into a comprehensive picture of any person’s life—automatically and at massive scale.
• Fully autonomous weapons. Partially autonomous weapons, like those used today in Ukraine, are vital to the defense of democracy. Even fully autonomous weapons (those that take humans out of the loop entirely and automate selecting and engaging targets) may prove critical for our national defense. But today, frontier AI systems are simply not reliable enough to power fully autonomous weapons. We will not knowingly provide a product that puts America’s warfighters and civilians at risk. We have offered to work directly with the Department of War on R&D to improve the reliability of these systems, but they have not accepted this offer. In addition, without proper oversight, fully autonomous weapons cannot be relied upon to exercise the critical judgment that our highly trained, professional troops exhibit every day. They need to be deployed with proper guardrails, which don’t exist today.

To our knowledge, these two exceptions have not been a barrier to accelerating the adoption and use of our models within our armed forces to date.

The Department of War has stated they will only contract with AI companies who accede to “any lawful use” and remove safeguards in the cases mentioned above. They have threatened to remove us from their systems if we maintain these safeguards; they have also threatened to designate us a “supply chain risk”—a label reserved for US adversaries, never before applied to an American company—and to invoke the Defense Production Act to force the safeguards’ removal. These latter two threats are inherently contradictory: one labels us a security risk; the other labels Claude as essential to national security.

Regardless, these threats do not change our position: we cannot in good conscience accede to their request.

It is the Department’s prerogative to select contractors most aligned with their vision. But given the substantial value that Anthropic’s technology provides to our armed forces, we hope they reconsider. Our strong preference is to continue to serve the Department and our warfighters—with our two requested safeguards in place. Should the Department choose to offboard Anthropic, we will work to enable a smooth transition to another provider, avoiding any disruption to ongoing military planning, operations, or other critical missions. Our models will be available on the expansive terms we have proposed for as long as required.

We remain ready to continue our work to support the national security of the United States.