The 8 Best Computer Use APIs in 2026: Benchmarks, Pricing and Trade-offs

What is a computer use API?

A computer use API lets an AI model operate a computer the way a person does: it looks at the screen, then clicks, types, scrolls and runs commands to finish a task. It reaches software that has no API of its own, such as legacy desktop apps and internal portals (The Case for GUI Agents).

Computer use APIs come in two shapes. Model-level tools (Anthropic, OpenAI, Google) return actions; you host the machine and run the loop. Managed agent APIs (Sai, Amazon Nova Act, Browser Use Cloud) run the machine and the loop for you and return results.

Quick picks

1. Best managed API for full desktop work: Sai API by Simular
2. Best model-level tool for desktop control: Anthropic computer use
3. Best for code-driven automation: OpenAI computer use
4. Best for browser plus Android: Gemini computer use
5. Best for AWS teams automating browsers: Amazon Nova Act
6. Best open-source browser agent: Browser Use
7. Best open-weight GUI model: UI-TARS-2
8. Best open-source desktop agent framework: Agent S

To provide an objective, actionable assessment for engineering leads, platform teams and technical founders choosing a computer use API, our evaluation framework assessed each platform across five standardized operational criteria:

1. Environment Coverage & Native Desktop Reach: Can the API operate full desktop applications on Windows, macOS and Linux, or is it confined to a browser tab or a single Linux container? Does it reach legacy line-of-business software, internal portals and Android, or only public websites?
2. Benchmark-Verified Reliability on Long-Horizon Tasks: How does the system perform on standardized evaluations of real computer work, such as OSWorld 1.0, the long-horizon OSWorld 2.0, WindowsAgentArena and AndroidWorld? We record which benchmark version was used and who reported each score, and we weight full-task completion and repeat-run consistency over single lucky runs.
3. Infrastructure Ownership & Developer Overhead: Who provisions and runs the machine? Does the API return finished results from managed computers, or does your team have to build the virtual display, screenshot loop, action handlers, session state and error recovery from scratch?
4. Total Cost of Ownership & Pricing Transparency: We analyzed true commercial costs: per-token model pricing, per-hour or per-task billing, hosting and GPU costs for self-run models, and published cost-per-task data. We also checked whether repeated workflows get cheaper over time or pay full reasoning cost on every run.
5. Safety Guardrails, Human-in-the-Loop & Governance: Does the platform pause for human approval before consequential actions such as payments, account changes or outbound messages? Does it offer prompt-injection defenses, isolated execution environments, data-retention controls and auditability suitable for production?

8 best computer use APIs

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1. Sai API by Simular — best managed API for full desktop work

The Sai API sends a task to Sai, Simular's computer-use agent, and streams back progress and results. Sai runs on a Simular cloud computer or on your own Mac or Windows machine, and works across desktop apps, browsers, file systems and terminals (Sai pricing FAQ).

• How it works: POST a task to /v1/agents/message, then follow /v1/agents/events over Server-Sent Events until the session goes idle (docs). An MCP server, @simular-ai/sai-mcp, plugs Sai into Claude Code, Codex and Cursor.
• Architecture: a mixture of frontier and specialist models, with specialist models for locating UI elements and verifying results. Sai plans longer subtasks in Simulang code, using about 1.5x fewer model calls than pure models (Simular).
• Cost on repeat work: solved tasks compile to code and replay; Simular reports 90%+ token reduction and up to ~200x lower cost on recurring workflows (Simular).
• Benchmarks: 73.0% partial score on OSWorld 2.0 at $15.70 per task, per Simular.
• Safety: sensitive actions emit a data-approval-request event; approve via POST /approve or send a person to the approvalUrl.
• Limits: 60 messages per hour per user; 25 MB per uploaded file (Simular).
• Pricing: free plan with a pooled Windows cloud computer; $50/month pay-as-you-go; $500/month unlimited (pricing).
• Trade-off: a managed agent, not raw model access; you don't control each low-level action.

# Base URL per sai.work/api; confirm before publishing
curl -X POST "https://api.sai.simular.ai/v1/agents/message" \
  -H "Authorization: Bearer $SAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"message": "Download the Q3 sales report from the internal portal, total each column in Excel and save it.", "wait": false}'

# Then stream progress and results
curl -N "https://api.sai.simular.ai/v1/agents/events?sessionId=<sessionId>" \
  -H "Authorization: Bearer $SAI_API_KEY"

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2. Anthropic computer use — best model-level tool for desktop control

Anthropic's computer use tool gives Claude screenshots plus mouse and keyboard control. The current computer_toolset_20260801 is a production toolset of 17 member tools, including screenshot, left_click, type and zoom, with no beta header.

• Models: Claude Opus 4.8, 5 and 5.5; Sonnet 5 and 5.5; Fable 5/5.1 and Mythos 5/5.1.
• Platforms: Claude API, Google Cloud Vertex AI and Amazon Bedrock; AWS and Microsoft Foundry in beta.
• What you build: the sandboxed environment (Anthropic's reference uses Docker with a virtual X11 display), the agent loop and the action handlers. A reference implementation gets you started.
• Safety: prompt-injection classifiers run automatically; Anthropic advises a low-privilege VM, a domain allowlist, and human confirmation for consequential actions. Computer use is zero-data-retention eligible.
• Trade-off: maximum control and strong reasoning, but you own the infrastructure, session state and recovery logic.

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3. OpenAI computer use — best for code-driven automation

OpenAI's computer use API supports two approaches: the model writes code that drives Playwright or PyAutoGUI, or it returns structured mouse and keyboard actions through the computer tool. OpenAI recommends GPT-6 Astra for the code approach.

• Environments: browser (Playwright samples) and desktop (PyAutoGUI samples).
• What you build: the isolated environment, the API loop, screenshot capture and safety controls.
• Note: Operator, the consumer agent many older lists still review, was folded into ChatGPT agent and shut down on August 31, 2025 (OpenAI).
• Trade-off: the code-writing approach is efficient for repeatable flows, but you maintain the runtime.

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4. Gemini computer use — best for browser plus Android

Google's computer use tool works across browser, mobile (Android) and desktop environments using normalized 0–999 coordinates. Gemini 3.8 Flash is the recommended model; computer use became a built-in tool with Gemini 3.5 Flash in June 2026.

• Safety: built-in policies ask for user confirmation on purchases, sensitive data changes, communications, account creation and legal agreements; prompt-injection detection is opt-in.
• What you build: the client-side execution environment; Google provides a Docker-based reference.
• Trade-off: still labeled preview, and Google warns it "may contain errors and security vulnerabilities."

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5. Amazon Nova Act — best for AWS teams automating browsers

Amazon Nova Act is a managed service for building agents that automate browser workflows such as QA testing, form filling and data extraction. It became generally available on December 2, 2025 and deploys to Bedrock AgentCore Runtime.

• Pricing: $4.75 per agent hour of active work; time waiting on humans is excluded (Classmethod).
• Trade-off: browser-focused; at GA it ran only in US East (N. Virginia).

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6. Browser Use — best open-source browser agent

Browser Use is an MIT-licensed library that connects any LLM to a browser, with a hosted cloud for agents and remote browsers. The project reports 117k GitHub stars and 7.4M monthly downloads.

• Benchmarks: on its BU Bench V1, Claude Fable 5 with the open-source library scored 80.0% and Browser Use Cloud 78.0% (Browser Use).
• Pricing: library free; cloud agents cost model price +20% plus browser time; browsers from $0.02/hour.
• Trade-off: browser only; no native desktop apps.

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7. UI-TARS-2 by ByteDance — best open-weight GUI model

UI-TARS is an Apache-2.0 family of GUI agent models. UI-TARS-2 (September 2025) reports 47.5% on OSWorld, 50.6% on WindowsAgentArena, 73.3% on AndroidWorld and 88.2 on Online-Mind2Web (arXiv). The UI-TARS-1.5-7B model is small enough for a single GPU.

• Best for: on-premise or air-gapped deployments and research.
• Trade-off: you host the model, the environment and the recovery logic.

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8. Agent S by Simular — best open-source desktop agent framework

Agent S is Simular's Apache-2.0 framework for agents that use computers like a person, installable with pip install gui-agents. It runs on Linux, macOS and Windows and pairs a main model (OpenAI, Anthropic, Gemini and others) with a grounding model such as UI-TARS.

• Benchmarks: Agent S3 reported 72.6% on OSWorld 1.0 with best-of-N selection, above the 72.36% human baseline; 66% standalone at 100 steps; 56.6% on WindowsAgentArena and 71.6% on AndroidWorld (Simular).
• Trade-off: a research framework; for managed infrastructure and approvals, use the Sai API built on the same research.