I Compared Every Major Computer Use Agent in 2025. Most of Them Are Embarrassing.

The Benchmark That Exposes Everyone

OSWorld is the standard test for computer-using AI agents. It throws real desktop tasks at agents, things like navigating apps, filling forms, managing files, and doing multi-step workflows across real operating systems. No sandboxes. No rigged demos. Just the agent, a desktop, and a task to complete. The scores tell a brutal story. When OpenAI first launched its Computer-Using Agent, it scored 38.1% on OSWorld. Anthropic's Computer Use, at its early release, scored around 22%. That means Anthropic's flagship computer use product was failing on roughly 78 out of every 100 tasks. And these companies were charging enterprise rates and doing press tours about it. Claude Sonnet 4.5 eventually climbed to 61.4% on OSWorld, which is real progress. But here's the thing: 61% still means your AI agent is confidently failing on nearly 4 out of 10 tasks. In a business setting, that's not a tool. That's a liability.

OpenAI Operator: A $200/Month Product That Couldn't Order Groceries

I want to talk about the grocery test because it perfectly captures where most computer use agents are right now. A reviewer at Understanding AI gave Operator a simple task in mid-2025: order groceries. Operator failed. It couldn't transcribe items correctly from a list. It got confused by basic UI interactions. This is the product OpenAI launched with a massive press event, requiring a $200 per month ChatGPT Pro subscription. The Washington Post ran a piece in early 2025 asking whether Operator was 'ready for the real world.' The polite answer was no. A Reddit thread from July 2025, where someone stress-tested the ChatGPT Agent on shopping and travel tasks, got 3,300 upvotes. The top comment was essentially: 'cool demo, useless in practice.' That's not a niche complaint. That's the consensus from real users putting real money down. Operator is a fine research project. It is not a production tool.

UiPath: The Legacy Player That Built a Bot to Fix Its Own Broken Bots

UiPath is the old guard of automation. They've been selling RPA to enterprises for years. And to be fair, they've done real work trying to evolve. Their Screen Agent, powered by Claude Opus 4.5, actually earned a top OSWorld-Verified ranking in January 2026, which is legitimately impressive. But here's what I can't get past: in July 2025, UiPath published a blog post introducing their 'Healing Agent,' a separate AI system whose entire job is to fix the failures of their existing automation bots when UI elements change or break. Think about that. They needed to build a second agent to babysit the first agent. That's not a feature. That's an admission. Traditional RPA has always had this problem. You build a bot that clicks button X on screen Y. Someone updates the software. Button X moves. Bot breaks. IT ticket gets filed. Someone fixes it manually. The whole value proposition collapses. UiPath knows this. That's why they built the Healing Agent. It's clever engineering, but it's also a band-aid on a model that was never designed for the dynamic, messy reality of modern software environments.

The Real Cost of 'Good Enough' Automation

• ●Workers spend an average of 4 hours and 38 minutes per week on duplicate, repetitive tasks, according to Clockify's 2025 research.
• ●92% of workers say automation increased their productivity, but most companies still haven't deployed anything that actually works end-to-end.
• ●Anthropic Computer Use launched with a 22% OSWorld score. That's lower than most people's exam passing grade.
• ●OpenAI Operator required a $200/month subscription at launch and still failed basic real-world tasks in independent reviews.
• ●UiPath's own blog admits UI automation failure rates are a 'significant issue' for enterprises, hence the Healing Agent product.
• ●The average employee spends 1.5 hours per week just on copy-pasting data between apps. Multiply that across a 500-person company and you're looking at 750 hours of pure waste every single week.
• ●AI agents that score under 60% on OSWorld are, statistically, more disruptive than helpful in high-volume workflows because you spend more time checking their work than doing it yourself.

What a Computer Use Agent Actually Needs to Do

Here's where most comparisons go wrong. They test agents on cherry-picked tasks in clean environments. Real computer use is not clean. Real computer use is a finance analyst who needs to pull data from a legacy web portal, paste it into Excel, reformat it, upload it to a reporting tool, and send a summary email. That's five apps, multiple UI interactions, and zero tolerance for the agent getting confused halfway through and clicking the wrong button. The best computer-using AI systems need to do three things well. First, they need to actually see and understand the screen, not just parse HTML or make API calls. Second, they need to recover gracefully when something unexpected happens. Third, they need to be fast enough to be worth using. Most agents fail on at least two of those three. The ones scoring in the 30s and 40s on OSWorld are failing on all three.

Why Coasty Exists

I'm not going to pretend I don't have a horse in this race. I work at Coasty. But I also wouldn't be here if I didn't think the product was genuinely better, and the numbers back that up. Coasty sits at 82% on OSWorld. That's not a rounding error above the competition. That's a different category of performance. Anthropic's best model recently hit 61.4%. The gap between 61% and 82% in real-world automation is enormous because failures compound. One wrong click in a multi-step workflow doesn't just fail that step. It corrupts every step after it. At 82% accuracy, Coasty is the only computer use agent on the market that you can actually trust with unsupervised, multi-step workflows. The architecture matters too. Coasty controls real desktops, real browsers, and real terminals. Not simulated environments. Not API wrappers pretending to be computer use. Actual screen control, the same way a human would operate a computer. It runs as a desktop app, supports cloud VMs for scaling, and can spin up agent swarms for parallel execution when you need to run the same workflow across hundreds of instances simultaneously. There's a free tier if you want to test it yourself, and BYOK support if you want to bring your own API keys. The reason Coasty exists is simple: every other computer use agent on this list is still in the 'impressive demo' phase. Coasty is in the 'ship it to production' phase.