You're Paying $200/Month for a Computer Use Agent That Fails 68% of the Time

OpenAI Operator: $200/Month for a 32.6% Success Rate

OpenAI Operator launched in January 2025 with a lot of fanfare and a $200/month price tag locked behind the ChatGPT Pro plan. That's $2,400 a year. For that money, you get a computer-using AI that scores 32.6% on OSWorld, the industry-standard benchmark for computer use agents. Human performance on OSWorld sits at 72.4%. So you're paying premium prices for a tool that performs less than half as well as a person. The New York Times called it 'brittle.' Reddit users who tested it found it couldn't handle JavaScript-heavy sites, couldn't make bookings or reservations, and basically worked on Wikipedia and some government pages. That's not a computer use agent. That's a very expensive search bar. To be fair, OpenAI has iterated since the original Operator launch, and the ChatGPT agent introduced in July 2025 added more agentic capabilities. But the core problem hasn't changed: the performance-to-price ratio is brutal, and you're still locked into their ecosystem with zero flexibility on model costs.

Anthropic Computer Use: Smart Model, Punishing Token Costs

Anthropic's computer use API is genuinely impressive from a research standpoint. Claude is a great model. But here's what nobody explains clearly before you start building with it: computer use agents consume orders of magnitude more tokens than a regular chatbot. Every action requires a screenshot. Every screenshot gets fed back into the model as a high-resolution image. Tasks that would cost pennies in a text-only workflow can cost dollars when you're running computer use. Claude Opus 4.5, their top agent-optimized model, runs at $15 input and $75 output per million tokens. A single moderately complex computer use task can easily burn through dozens of screenshots and thousands of tokens per step. Run a few hundred tasks a month and you're looking at costs that scale faster than your finance team will be comfortable with. Plus, Anthropic has been tightening usage limits without warning, something their own community called out loudly in late 2025. Building a production workflow on top of a platform that can quietly throttle you isn't a strategy. It's a gamble.

UiPath: The Legacy Tax You're Still Paying

• ●$1,380/month for just 1 unattended bot and 1 attended bot on their base plan, before you've automated a single real workflow
• ●Requires dedicated implementation teams, often months of setup, and specialized RPA developers who command $80,000-$120,000 salaries
• ●Built for structured, rule-based processes. The moment something on a webpage changes, the bot breaks and someone has to fix it manually
• ●Their 'agentic' pivot in 2025 is essentially legacy RPA with an AI wrapper bolted on, best suited for teams already deep in the UiPath ecosystem
• ●Total cost of ownership for a mid-size UiPath deployment routinely runs into six figures annually when you count licensing, maintenance, and developer time
• ●Compare that to a modern computer use agent that handles visual, unstructured tasks without brittle selectors or constant maintenance cycles

Why Computer Use Token Costs Are Worse Than Anyone Admits

Here's the thing that pricing pages don't show you. A computer use agent doesn't just call an API once per task. It takes a screenshot, sends it to the model, gets an action back, executes the action, takes another screenshot, sends that to the model, and repeats. For a task with 20 steps, that's 20 screenshots minimum. Research published in late 2025 confirmed that computer-use agents have 'very high task token consumption' specifically because of screen recognition overhead. One LinkedIn analysis from January 2026 put the RAM and compute requirements for production computer use at 200GB+ just for the infrastructure side. This is why BYOK (bring your own key) support matters so much. If you're locked into a vendor's token pricing with no ability to swap models or control costs, you're at their mercy every time they decide to reprice. And they will reprice. Anthropic already did it with Haiku. OpenAI cut o3 prices by 80% in June 2025, which sounds great until you realize the original price was just that inflated to begin with.

Why Coasty Is the Answer to This Pricing Mess

I'm going to be straight with you. I work at Coasty. But the reason I work here is because the product actually solves the problem I just spent 600 words describing. Coasty scores 82% on OSWorld. That's not a marketing number. That's the benchmark everyone in the computer use space uses to measure performance, and 82% is higher than every competitor, including the ones charging $200/month for a third of that score. Coasty controls real desktops, real browsers, and real terminals. Not sandboxed browser sessions. Not API call wrappers pretending to be agents. Actual computer use, the way it needs to work in production. The pricing model is also built for reality. There's a free tier so you can test it before committing to anything. BYOK is supported, meaning you can bring your own API keys and control your own model costs instead of getting locked into someone else's token pricing. And for teams that need to run tasks in parallel, agent swarms on cloud VMs let you scale without the per-bot licensing nightmare that makes UiPath so painful. The gap between 82% and 32.6% on OSWorld isn't a small edge. It's the difference between an agent that actually finishes your tasks and one that fails two-thirds of the time and still charges you for the attempt.