Reliable
Every step is checked before the next
Independent Judges read the screen and confirm a step worked before Sai moves on. That is how Sai reached 79.38% on OSWorld 2.1, the highest partial score on the official leaderboard.
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Simular API vs OpenAI Computer Use
OpenAI Computer Use is a computer tool in the Responses API: GPT models request clicks and keystrokes, and you provide the browser or VM and run the loop that executes them. The Simular API gives you the finished agent on a ready computer. Send a task in plain English and get the result back.
- Highest partial score on OSWorld 2.1
- 79.38%
- per task, the only cost published on the leaderboard
- $14.34
- to add Sai to Claude Code, Codex or Cursor
- 1 command
Simular API vs OpenAI Computer Use, side by side
As of October 2026
| Capability | Simular API | OpenAI Computer Use |
|---|---|---|
| What you get | ||
| Product | A working computer-use agent (Sai) behind one API | A model plus a computer tool in the Responses API (no hosted agent) |
| Computer included | Hosted Windows cloud computer, or your own Mac or Windows with the Sai desktop app | No. You provide and run the browser or VM |
| Operating systems | Windows in the cloud; macOS and Windows on your own machine. No Linux | Any you provide: browser, Windows, macOS, Linux |
| Native desktop apps | Yes: desktop apps on Windows and macOS, not just a browser | Yes, if you provide a desktop (e.g. via PyAutoGUI) |
| Agent loop and action execution | Built in: send a task in plain English, get the result | No. You run the loop; the Agents SDK helps but you implement the Computer interface |
| Setup / time to first task | Create an API key, add one MCP command (about a minute) | Build the sandbox, screenshot capture, action runner, loop and safety checks |
| Reliability and cost | ||
| Benchmark | Highest partial score on the official OSWorld 2.1 leaderboard: 79.38% (Sai w/ Claude Opus 5, 500 steps, Oct 2026). Binary success 41.67%, #2 behind Claude Opus 5 (44.33%). Trajectories public on Hugging Face | OSWorld 2.0 (offline, partial): GPT-6 Astra 72.6% (Sep 2026). OSWorld-Verified: GPT-5.4 75.0% (Mar 2026) |
| Step verification | Independent Judges check the screen before each next step | Not built in; up to your loop |
| Pricing | Credits per request. Free plan: one shared Windows cloud computer with daily limits. Paid: dedicated computers and top-ups. | Per token, no separate tool fee: gpt-6-astra $10 in / $50 out; gpt-6.1-sol $2 / $10 per 1M |
| Cost per task / cost drivers | $14.34 per OSWorld 2.1 task, the only leaderboard entry with a published cost (OSWorld 2.0: $15.70) | Screenshot image tokens each turn (full resolution recommended), reasoning tokens, turns, plus your compute |
| Repeat runs | Learns a workflow once, then replays it as self-healing code: up to 90% fewer tokens on repetitive tasks | Prompt caching discounts only; no workflow replay |
| Control and safety | ||
| Human approval | Built in: approve, approve for this task, or deny; link-only approvals for sign-ins and credentials | pending_safety_checks must be acknowledged; confirmation UI is yours to build |
| Live view / takeover | Live view to watch tasks and answer approvals. No manual takeover | None from OpenAI; the sample app has an operator console with replay artifacts |
| Data and compliance | SOC 2 Type II and HIPAA. Runs on Simular's cloud computer or your own machine. | Machine stays in your infra; 30-day abuse retention by default; ZDR eligible; data residency options |
| Operations | ||
| Sessions and persistence | Context carries across tasks on a computer; reset with new-session. | No server-side VM session; you keep the environment alive between calls |
| Concurrency and limits | One task per computer at a time; 60 messages per hour; paid plans add dedicated computers | Standard model rate limits by tier (gpt-6-astra up to 15K RPM at Tier 5) plus your infra |
| Fit in your stack | ||
| Coding agents / MCP | Official MCP server (@simular-ai/sai-mcp) for Claude Code, Codex, Cursor and any stdio MCP client | No official computer-use MCP server found (Codex covered separately) |
| Model choice | Model-agnostic: Anthropic, OpenAI, Google, MiniMax, xAI, OpenRouter, or auto | OpenAI models only (GPT-6 Astra recommended) |
| SDKs / languages | HTTP API (curl, Python, Node examples) plus the MCP server on npm | Responses API with official SDKs; Agents SDK in Python and TypeScript |
| Free tier | Yes: free plan includes a shared Windows cloud computer (daily limits) | No free API tier for computer-use-capable models |
What unifies the Simular API
Four things every task gets, without extra code.
Efficient
Learn once, repeat for less
The first run works the task out. After that, Sai replays it as self-healing code instead of reasoning through every screen, using up to 90% fewer tokens on repetitive tasks.
Ready
A whole computer, already running
Sai works on a hosted Windows cloud computer, or on your own Mac or Windows machine. It opens apps, clicks and types in desktop software that has no API. No VMs or display drivers to manage.
Composable
Plugs into the agents you already use
Add Sai to Claude Code, Codex or Cursor with one MCP command, or call one HTTP endpoint from any language. It pauses for your approval before sign-ins and other sensitive steps.
Frequently asked questions
What is the difference between the Simular API and OpenAI Computer Use?
OpenAI Computer Use is a computer tool in the Responses API. The model returns computer_call actions, and your code runs the browser or VM, executes each action and sends back a screenshot until the task is done. The Simular API is a complete agent: you send a task in plain English and Sai does the work on a ready computer, with step checks and approvals built in.
Is computer-use-preview still available?
No. OpenAI has deprecated the computer-use-preview (CUA) model. Computer use now runs through the computer tool with newer models such as GPT-6 Astra, which OpenAI recommends for computer use.
How much does OpenAI Computer Use cost?
There is no separate tool fee: you pay per token, including the screenshot image tokens sent each turn, reasoning tokens and the number of turns, plus the compute you run the environment on. The Simular API is billed in credits per request, and on OSWorld 2.1 Sai completed tasks at $14.34 each, the only cost published on the leaderboard.
Do I need to build my own sandbox for OpenAI Computer Use?
Yes. You build the sandbox, screenshot capture, action runner, loop and safety checks; OpenAI publishes a sample app with an operator console to start from. With the Simular API the computer is included: a hosted Windows cloud computer, or your own Mac or Windows machine with the Sai desktop app.
Can I use GPT models with the Simular API?
Yes. The Simular API is model-agnostic: OpenAI, Anthropic, Google, MiniMax, xAI and OpenRouter models, or auto.
How do the benchmark scores compare?
Sai’s 79.38% is the highest partial score on the official OSWorld 2.1 leaderboard. OpenAI publishes its figures on OSWorld 2.0 (GPT-6 Astra, 72.6%) and OSWorld-Verified (GPT-5.4, 75.0%). These are different versions of the benchmark, so the numbers are not directly comparable.
When is OpenAI Computer Use the better choice?
When you want full control of the OS and infrastructure, zero data retention and data residency options, low-cost models, or a code mode built on Playwright or PyAutoGUI. Choose the Simular API when you want a working agent without building the sandbox, loop and confirmation flow yourself.
How do I get started with the Simular API?
Sign in at platform.simular.ai and create an API key. Add Sai to Claude Code, Codex or Cursor with one MCP command, or call the HTTP API from any language. The free plan includes a shared Windows cloud computer with daily limits.
Skip the harness. Ship the agent.
Get an API key in a minute, or talk to us about running Sai at scale.