Computer Use Agent Pricing in 2025: You're Getting Ripped Off and You Don't Even Know It

The Token Tax: What Anthropic Computer Use Actually Costs You

Claude's computer use capability is real and it's impressive on paper. Anthropic has been shipping hard. Claude Sonnet 4.5 hit 61.4% on OSWorld. But here's the thing nobody in the press releases mentions: computer use is brutally token-hungry. Every screenshot the model takes to understand what's on screen gets processed as input tokens. Every action, every verification, every correction loop burns more. You're not paying for a task. You're paying for every single cognitive step the model takes to complete that task, whether it succeeds or not. Claude Sonnet 4.6 pricing sits at roughly $3 per million input tokens and $15 per million output tokens. Sounds cheap until your agent is taking 40 screenshots to fill out a form that a human would knock out in 90 seconds. The token tax is real, it's invisible in demos, and it compounds fast at scale. Anthropic themselves admit in published documentation that computer use is 'slow and often error-prone at the cutting edge.' That's a direct quote from their own ecosystem commentary. You're paying premium token rates for a product that the people who built it describe as error-prone. Think about that.

OpenAI Operator: $200 a Month to Watch an Agent Fail Silently

OpenAI Operator launched in January 2025 with a lot of fanfare and a $200 per month price tag for ChatGPT Pro access. Real users testing it reported some genuinely painful experiences. One widely shared Reddit thread from July 2025 catalogued what you get for that $200: it can't book travel, it can't make reservations, it burns tokens at a rate you can't track, and it fails silently unless you manually force it to report errors. A Medium piece from early in the year called it 'research mode,' which is a polite way of saying it's not production-ready. To be fair, OpenAI has been iterating. But the core problem with Operator as a computer use agent isn't the intelligence, it's the architecture. It's a browser-only agent bolted onto a chat product. It doesn't control a real desktop. It can't touch native applications. It can't run terminal commands. For anything beyond basic web browsing automation, you've already hit the ceiling, and you're still paying $200 a month for the privilege of finding that out.

UiPath: The $100,000 Hammer for a $10 Nail

• ●UiPath enterprise licensing is notoriously opaque. Forum users in mid-2025 described license structures so complex they needed dedicated internal staff just to manage the entitlements.
• ●One Reddit thread on r/rpa described UiPath costs as 'really expensive' with rough math suggesting hundreds of thousands in annual spend for mid-sized deployments, before implementation costs.
• ●Traditional RPA like UiPath requires dedicated bot infrastructure, maintenance engineers, and constant script updates every time a UI changes. A website redesign can break dozens of automations overnight.
• ●Gartner and Forrester data from 2025 consistently point to strategic failure as the primary driver of automation project failures, not technical limits. Meaning: the tools are hard to deploy correctly, and vendors don't help you enough.
• ●UiPath is now pivoting hard to 'agentic automation' because they know the old script-based RPA model is dying. They're charging enterprise prices to retool for a future they weren't built for.
• ●The total cost of ownership for traditional RPA, including licenses, implementation, and maintenance, routinely runs 5 to 10 times the initial quote. Ask anyone who's actually deployed it at scale.

The Benchmark Nobody Wants to Talk About

OSWorld is the gold standard for measuring what a computer use agent can actually do on a real desktop with real applications. Not cherry-picked demos. Not curated API calls. Real tasks, real interfaces, real failure modes. Claude Sonnet 4.5 scores 61.4%. That's actually decent, and Anthropic deserves credit for the progress. OpenAI's CUA model has been benchmarked in the mid-to-high 30s to low 40s range on comparable tasks depending on the evaluation setup. Most enterprise RPA tools don't even submit to OSWorld because the benchmark would expose how brittle script-based automation really is when the environment isn't perfectly controlled. Then there's Coasty, sitting at 82% on OSWorld. That's not a rounding error advantage. That's a different category of capability. When you're at 82% versus a competitor at 61%, you're not just doing the same tasks slightly better. You're completing tasks the others simply abandon or fail. At scale, across thousands of automated workflows, that gap translates directly into dollars saved and hours recovered.

Why Coasty Exists and What It Actually Changes

Coasty was built specifically as a computer use agent, not as a chatbot that learned some desktop tricks. That distinction matters more than most people realize. It controls real desktops, real browsers, and real terminals. It's not making API calls and pretending to interact with software. It's actually using the computer the way a human operator would, which means it works on legacy applications, internal tools, custom software, anything with a screen. The 82% OSWorld score isn't marketing. It's the highest published score on the benchmark, period. Nobody else is close right now. The pricing model is also built for the real world. There's a free tier to actually test it, BYOK support so you're not locked into one inference provider's token rates, and agent swarms for parallel execution when you need to run the same workflow across hundreds of instances simultaneously. That last part is where the economics get genuinely interesting. If you're paying $28,500 per employee per year in manual task costs, and you can run parallel computer use agents at a fraction of that cost with an 82% success rate on complex multi-step tasks, the ROI conversation becomes very short. The question isn't whether you can afford to use a proper computer use agent. It's whether you can afford not to.