In October 2025, Anthropic released Computer Use, letting Claude "see the screen, click the mouse, type on the keyboard" to operate a computer directly. Less than a year later, OpenAI's Operator/CUA and Google's Project Mariner followed suit, and the open-source side produced three 10k-star contenders: trycua/cua at 21k stars, simular-ai/Agent-S at 12k, and microsoft/fara at 6k. AI has officially crossed from "can chat" to "can work"-but if you actually want to pick one to operate your computer, which of the three closed-source giants and three open-source challengers is more reliable? This review lays them all side by side.
Scope first: this is based on each tool's GitHub README, official site, and public benchmarks, as of 2026-08-11. Open-source star counts verified via GitHub API (cua 21,113 stars, Agent-S 12,147 stars, fara 6,140 stars); closed-source tools have no public repos so no star counts, and pricing and availability are per each official site. This is a representative comparison, not a personal full-scale benchmark. This site also published the Gemini Robotics ER-2 hotspot (another thread in embodied AI), the cua open-source resource (dedicated open-source piece), and the computer-use agent build SOP (how to build after you pick)-this piece covers the "selection" step.
One: Know the Difference-Computer Use Is Not RPA, Nor a Personal Assistant
Three easily confused concepts, demarcated first. Computer Use / GUI Agent: the AI uses visual recognition of screen screenshots plus simulated mouse and keyboard input to operate a graphical interface like a human-any button you can click, any form you can fill, it can operate, without depending on the software exposing an API. RPA (Robotic Process Automation): relies on recording or scripts to click along a fixed path, with no "understanding" capability-once the flow changes, it breaks. Personal assistants (e.g., OpenClaw): run locally, operating email/calendar/files/terminal via API calls and scripts rather than "seeing the screen"-this site covered it in the OpenClaw resource; it does not belong to GUI computer-use and is excluded from this comparison. This piece only compares the "watch screen, move mouse" category.
Two: Capability Matrix-Six-Tool Specs Table
Six representative tools, compared across positioning, open-source status, supported OS or browser, and core capability.
| Tool | Positioning | Open source | Supported OS/Browser | Core capability |
|---|---|---|---|---|
| Claude Computer Use | Desktop-first GUI agent | No | Desktop (cross-app) + Web | Screenshot recognition + mouse/keyboard simulation, cross-app workflows |
| OpenAI Operator/CUA | Browser-first cloud agent | No | Cloud virtual browser | Web task automation, cloud-isolated execution |
| Google Project Mariner | In-browser agent | No | Chrome browser | Browser-anchored automation, Google ecosystem integration |
| trycua/cua | Cross-OS open-source computer-use | Yes (MIT) | macOS/Windows | computer-use 2.0, cross-OS local control |
| simular-ai/Agent-S | Open-source agentic framework | Yes (Apache-2.0) | macOS/Windows/Linux | Framework that uses computers like a human, customizable |
| microsoft/fara | Open-source computer-use model | Yes (MIT) | Cross-platform (model-level) | Fara1.5 frontier computer-use agent model |
A few clarifications. First, the three closed-source players take different architecture routes: Anthropic is desktop-first (broadest cross-app reach), OpenAI is browser-first (most secure via cloud isolation but limited to web), and Google is browser-anchored (in between, winning on ecosystem). Second, the three open-source tools occupy different layers: cua is a ready-to-use cross-OS tool, Agent-S is a customizable framework, and fara is model-level (you build the screenshot and operation pipeline yourself). Third, "open source" does not mean "zero cost"-the software is free, but you pay for LLM API calls or local compute.
Three: One by One-Each Tool's Best Range
Claude Computer Use: strongest cross-app, desktop-first. From Anthropic, provided as a computer-use tool via the Claude API. The model takes a screenshot to "see" the screen, outputs mouse coordinates and keyboard instructions, and directly operates the local desktop-without depending on software APIs; theoretically any software you can use, it can use. Its strength is cross-app versatility: scraping data from a web page into Excel, moving information across windows, operating legacy software with no API-this is its home turf. Shortcomings: slow (each step requires screenshot + reasoning + action), non-trivial error rate on complex multi-step tasks, and Chinese-language software compatibility remains unverified. Best for: cross-app information transfer, complex desktop workflows. Pricing is per Claude API usage, per the official site. China availability: API requires VPN, restricted.
OpenAI Operator/CUA: most stable for browser tasks, cloud-isolated. OpenAI's Computer-Using Agent runs all operations in a server-side virtual browser-it never touches your local computer, which is secure but limits it to web apps. Its strength is stable web task execution: booking flights, filling forms, price comparison, information retrieval, all run in the cloud with results returned. Shortcoming: the browser-first architecture limits desktop app operation-it can't reach your local Excel or WeChat. Best for: web task automation, online forms, information retrieval. Pricing via ChatGPT Pro subscription, per the official site. China availability: ChatGPT is unavailable in China.
Google Project Mariner: in-browser agent, wins on ecosystem. Google's solution, anchored in the browser, deeply integrated with the Google ecosystem (Gmail, Docs, Search). Its strength is smooth task execution within Google services. Shortcomings: weak desktop operation capability, and abilities are locked inside the Google ecosystem. Best for: browser automation for heavy Google ecosystem users. Pricing per the official site. China availability: Google services are restricted in China.
trycua/cua: open-source cross-OS, ready to use. 21,113 stars, MIT license. computer-use 2.0, supporting macOS and Windows cross-OS control-the highest-starred and most-watched open-source contender, with a dedicated open-source piece on this site. Its strengths are cross-OS + open source + self-hostable: you can run it entirely locally, with data never leaving your machine. Shortcomings: requires self-installation and configuration, model costs are on you, and stability varies. Best for: developers who want local, cross-OS automation. China availability: open source, runs locally, unrestricted.
simular-ai/Agent-S: open-source framework, customizable. 12,147 stars, Apache-2.0. Positioned as "an agentic framework that uses computers like a human"-not just a tool, but a framework for building custom computer-use agents, supporting macOS/Windows/Linux. Its strength is customizability: modifying interaction logic, plugging in your own model, adding safety boundaries-framework-level solutions are the most flexible. Shortcoming: higher barrier than cua, requires writing code. Best for: developers building custom computer-use agents. China availability: open source, runs locally, unrestricted.
microsoft/fara: Microsoft's official open-source model. 6,140 stars, MIT. Fara1.5 is a frontier computer-use agent model-note that it is a "model" rather than a "tool"; you build the surrounding screenshot and operation pipeline yourself. Its strengths are official Microsoft backing plus model-level capability: suited for researching frontier computer-use models or swapping models in your own pipeline. Shortcoming: model-level means more integration work, not ready to use like cua. Best for: research and engineering teams working with frontier computer-use models. China availability: open source, model can run locally.
Four: Pricing and Availability
The second table looks at go-to-market: free tier, paid, and China availability. Closed-source pricing is uniformly "per official site"-no invented numbers.
| Tool | Free tier | Paid | China availability |
|---|---|---|---|
| Claude Computer Use | None | Claude API pay-per-use (per official site) | Restricted, API needs VPN |
| OpenAI Operator/CUA | None | ChatGPT Pro subscription (per official site) | Unavailable |
| Google Project Mariner | None | Per official site | Restricted |
| trycua/cua | Open-source free | Model costs on you (API or local compute) | Available, runs locally |
| simular-ai/Agent-S | Open-source free | Model costs on you | Available, runs locally |
| microsoft/fara | Open-source free | Model costs on you | Available, runs locally |
The conclusion is straightforward: all three closed-source tools are restricted or unavailable in China, while all three open-source tools run locally without restriction-this is the biggest dividing line for developers in China. Closed-source wins on out-of-the-box readiness and model capability; open-source wins on autonomy and zero software cost.
Five: Selection Advice-Pick by Need
Direct conclusions by your need.
| Your need | Top pick | Reason |
|---|---|---|
| Cross-app desktop workflow automation | Claude Computer Use | Desktop-first, strongest cross-app capability |
| Web task automation (booking/forms/comparison) | OpenAI Operator/CUA | Browser-first, cloud isolation most stable |
| In-browser automation within Google ecosystem | Google Project Mariner | Deep integration with Google services |
| Local cross-OS automation (macOS/Windows) | trycua/cua | Highest open-source stars, ready to use |
| Build a custom computer-use agent | simular-ai/Agent-S | Framework-level, most customizable |
| Research frontier computer-use models | microsoft/fara | Microsoft-backed, model-level |
| China-available + data stays local | Any of the three open-source | Runs locally, unrestricted |
Most developers' actual combo: one closed-source tool as primary (Claude or Operator) + one open-source tool as local backup (cua is easiest to start with). No need to try all six-pick by your scenario and region.
Six: Three Pitfalls
One: Don't take benchmarks as the whole story-real success rates are still low. Public benchmark reports show that the best-performing open-source agent (Agent-S's S2 version) achieved only about 34.5% success rate within 50 steps-nearly two-thirds of tasks could not be completed. All agents perform poorly when limited to 15 steps; multi-step reasoning and planning remain the bottleneck. Allowing more steps improves success rates, but at the cost of higher latency and cost. Bottom line: today's computer-use agents can work, but don't expect them to get it right in one shot-plan for human review.
Two: Closed-source isn't "better," open-source isn't "worse." Closed-source wins on model capability and out-of-the-box readiness, but is unavailable in China, sends data off your machine, and has opaque pricing; open-source wins on autonomy and local execution, but requires self-setup, model costs on you, and stability varies. Choose by region, privacy requirements, and technical ability-don't just take sides along "closed vs. open."
Three: Always require human confirmation for sensitive operations. The ability to operate a computer equals the ability to cause harm. Banking, payments, and internal company systems should always be operated manually or at least confirmed by a human before execution. The safety red line in the Computer Use era is: sandbox first + operation allowlist + human confirmation for sensitive steps. This site's computer-use agent build SOP has the complete secure setup process.
Seven: FAQ
Q: What's the difference between Computer Use and RPA? A: RPA relies on recording or scripts to click along a fixed path, with no "understanding" capability-once the flow changes, it breaks. Computer Use uses a visual model to "see" the screen and reason about actions, handling interface changes and non-standard scenarios. For simple, repetitive, fixed-flow tasks, choose RPA; for tasks that need to "understand the screen before acting," choose Computer Use.
Q: Are the three closed-source tools usable in China? A: All are restricted or unavailable. Claude Computer Use's API requires a VPN and is restricted, OpenAI Operator/CUA is unavailable in China via ChatGPT Pro, and Google Project Mariner is restricted with Google services. Developers in China should look at the three open-source options first-they run locally without restriction.
Q: How do I choose among the three open-source tools? A: Depends on what you need. cua (21,113 stars) is ready to use, cross-OS, and easiest to start with; Agent-S (12,147 stars) is a framework, suited for developers building custom agents; fara (6,140 stars) is a model, suited for teams researching frontier computer-use models. Beginners start with cua, advanced users pick Agent-S, researchers pick fara.
Q: Can I use it for banking or payments? A: Not recommended. The ability to operate a computer equals the ability to cause harm-banking, payments, and internal company systems should always be operated manually or at least confirmed by a human before execution. Computer Use is suited for information transfer, form filling, and data cleanup-scenarios where "nothing major can go wrong." For anything involving real money, keep a human in the loop.
Q: Is it mature enough to do my job for me yet? A: Not quite. The best open-source agent has about a 34.5% success rate within 50 steps, with a high error rate on complex multi-step tasks. Its current positioning is "assistant" not "replacement"-it can handle repetitive, well-defined work, but you need to decompose tasks, allow room for trial and error, and do human review. Use it as a "digital intern," not a "digital substitute."
References
- Claude Computer Use (Anthropic) official site
- OpenAI Operator / CUA official site
- Google Project Mariner official blog
- trycua/cua GitHub (21,113 stars, MIT)
- simular-ai/Agent-S GitHub (12,147 stars, Apache-2.0)
- microsoft/fara GitHub (6,140 stars, MIT)
- This site: Gemini Robotics ER-2 hotspot | cua open-source resource | Computer-Use Agent Build SOP | Computer Use Era hotspot