You're Getting Robbed: The Real Cost of Every Computer Use Agent in 2026

The RPA Dinosaurs Are Still Charging Like It's 2018

Let's start with the legacy players, because the numbers are genuinely offensive. UiPath charges $1,380 per month for a single unattended bot plus one attended bot. One bot. Not a fleet of agents running in parallel, not an intelligent system that adapts to UI changes, just one fragile script-runner that breaks every time someone moves a button on the screen. Annual enterprise packages start climbing fast from there, and the 'contact sales' pricing wall means you won't know the real number until you're already three demos deep with a salesperson who plays golf with your CTO. The RPA model made sense in 2016 when AI was a research project. In 2026, paying five figures a year for brittle automation that can't handle a software update is just indefensible. These platforms built empires on implementation fees and maintenance contracts, and they have zero incentive to make things simpler or cheaper for you. The whole business model depends on your automation being hard to manage.

Anthropic and OpenAI: Great Models, Terrifying Token Bills

Here's where it gets spicy. Anthropic's Claude Sonnet 4.6 is priced at $3 per million input tokens and $15 per million output tokens. That sounds reasonable until you understand how computer use actually works. Every single action the agent takes requires a screenshot. Each screenshot is a large image that gets converted into tokens, and on top of that, the computer use tool itself adds extra input tokens per action. One user running an agentic task reported burning through 8 million tokens in a single session on Opus, racking up a bill that made them physically upset. Another developer reported their agent cost over $100 per day when first configured. Multiply that by a team of 20 people trying to automate their workflows and you're looking at a monthly AI bill that replaces the salary you were trying to avoid paying. OpenAI's Operator has its own set of problems. Real users who got early access reported it couldn't book travel, couldn't make reservations, and burned tokens at a rate with zero visibility into what was being consumed. One reviewer on Reddit flatly said it fails silently unless you force it to report back. You're paying for a $20 per month subscription on top of API costs, and what you get is an agent that gives up quietly and lets you think the task is done. That's not automation. That's expensive disappointment.

The Real Price You're Paying Isn't on Any Pricing Page

• ●UiPath unattended bot: $1,380 per month, per bot, before implementation costs, before maintenance, before the inevitable 'bot down' emergency at 2am
• ●Anthropic Claude computer use via API: $3 input / $15 output per million tokens, plus extra tokens per screenshot action, with no ceiling unless you set one manually
• ●OpenAI Operator: bundled into ChatGPT Pro at $200 per month, but reviewers report it fails silently on real tasks and has no token usage tracking built in
• ●Enterprise RPA annual costs range from $5,040 on the low end to well over $750 per bot per month at scale, with most companies running dozens of bots
• ●Over 40% of workers spend at least a quarter of their work week on manual repetitive tasks, meaning you're paying full salaries for part-time human output
• ●Human error rates in manual data entry run 1 to 5 percent, and in supply chain operations even small errors compound into massive downstream costs
• ●The average employee loses 4 hours and 38 minutes per week to duplicate and recurring tasks alone, which is more than 240 hours per year of pure waste
• ●Context switching costs workers five full working weeks per year according to Harvard Business Review, and no legacy RPA tool addresses that at all

Performance Matters Too, Because Cheap and Broken Is Worse Than Expensive

Pricing comparisons are useless if the tool can't actually do the job. This is where the conversation gets really uncomfortable for the big labs. Claude Sonnet 4.5 scored 61.4% on OSWorld, the gold-standard benchmark for real-world computer use tasks. That means nearly 4 out of every 10 tasks fail. You're paying per-token prices for an agent that succeeds about 60% of the time. OpenAI's computer-using agent benchmarks similarly in that range. These are not bad models, they're genuinely impressive pieces of technology, but the gap between benchmark scores and production reliability is real, and you feel it in your workflow every single day. When a computer use agent fails mid-task, it doesn't just waste the tokens it already burned. It can leave your system in a half-finished state, which means a human has to come in and clean up the mess. You've now paid for the AI attempt AND the human correction. The cost per successful task is much higher than the sticker price suggests.

Why Coasty Exists (and Why the Numbers Actually Make Sense)

Coasty was built specifically because the pricing and performance math on every existing computer use agent was broken. The benchmark result is 82% on OSWorld, which is the highest score of any computer use agent on the market right now, higher than every competitor including the big labs. That's not a rounding error kind of gap. That's the difference between an agent that actually ships work and one that fails on roughly a third of your tasks. The architecture matters here. Coasty controls real desktops, real browsers, and real terminals, not just API calls wrapped in an agent interface. It supports a desktop app, cloud VMs, and agent swarms for parallel execution, which means when you need to run the same task across 50 accounts or 50 files simultaneously, you're not waiting in a queue. You're running in parallel and finishing in a fraction of the time. On pricing, there's a free tier so you can actually test it before committing to anything. BYOK (bring your own key) is supported, which means you can use your existing model API relationships and control your token spend directly instead of paying a markup. The model is transparent. You know what you're paying and why. Compare that to UiPath's 'contact sales' wall or Anthropic's token meter that runs in the background while your agent clicks through screenshots. Coasty's pitch isn't 'trust us it's cheap.' It's 'here are the numbers, here is the benchmark score, go test it for free.' That's the kind of confidence you only have when the product actually works.