Three companies now offer AI agents that can use a computer: Microsoft’s Fara-7B, Anthropic’s Computer Use (via Claude), and OpenAI’s Operator. They all take screenshots and perform actions — but they differ dramatically in cost, capability, privacy, and deployment model.

Quick comparison

	Fara-7B	Anthropic Computer Use	OpenAI Operator
Developer	Microsoft Research	Anthropic	OpenAI
Model size	7B	Claude Sonnet/Opus (unknown, large)	GPT-4o+ (unknown, large)
Runs locally	✅ Yes	❌ Cloud only	❌ Cloud only
License	MIT (open source)	Proprietary API	Proprietary
Cost	Free (your hardware)	~$3-15 per task (API tokens)	$20-200/mo subscription
Privacy	Full — data stays local	Screenshots sent to Anthropic	Screenshots sent to OpenAI
WebVoyager score	73.5%	~85% (estimated)	Not published
Best for	Privacy, cost-sensitive, custom apps	Highest accuracy, complex tasks	Consumer convenience

Capability comparison

Task completion accuracy

Based on available benchmarks and real-world testing:

Simple tasks (search, navigate, fill a form):

• All three handle these well (>80% success)
• Fara-7B is slightly less reliable on unusual UI patterns

Medium tasks (multi-step shopping, booking with options):

• Anthropic Computer Use: ~85-90% success
• Fara-7B: ~70-75% success
• Operator: ~80% (estimated from user reports)

Complex tasks (multi-site research, tasks requiring judgment):

• Anthropic Computer Use: Best in class — Claude’s reasoning helps
• Fara-7B: Struggles with tasks requiring deep reasoning
• Operator: Good but sometimes gets stuck in loops

Speed

	Time per action	10-step task
Fara-7B (local, A100)	1-2 seconds	~15 seconds
Fara-7B (local, 4090)	2-3 seconds	~25 seconds
Anthropic Computer Use	3-5 seconds (network + inference)	~40 seconds
OpenAI Operator	2-4 seconds	~30 seconds

Fara-7B is fastest because there’s no network round-trip — everything happens on your GPU.

Supported actions

Action	Fara-7B	Anthropic	Operator
Click at coordinates	✅	✅	✅
Type text	✅	✅	✅
Scroll	✅	✅	✅
Navigate to URL	✅	✅	✅
Keyboard shortcuts	✅	✅	✅
Drag and drop	❌	✅	❌
File upload	❌	✅	✅
Multi-tab	❌	✅	✅

Cost analysis

Fara-7B: Free after hardware

• One-time cost: GPU ($1,500-$2,000 for RTX 4090) or cloud GPU ($1-3/hour)
• Per-task cost: $0 (electricity only)
• At scale: 1,000 tasks/day = $0/day (vs $3,000-15,000/day on Anthropic API)

Anthropic Computer Use: Pay per token

• Input: Screenshots are expensive (~1,000 tokens per image)
• Typical task: 5-15 screenshots + reasoning = $0.50-$3.00 per task
• Complex tasks: Can reach $10-15 with many steps
• At scale: Gets expensive fast

OpenAI Operator: Subscription

• ChatGPT Plus: $20/month (limited usage)
• ChatGPT Pro: $200/month (higher limits)
• No API access — can’t integrate into your own apps
• Best for: Personal use, not automation at scale

Privacy and security

	Fara-7B	Anthropic	Operator
Screenshots leave your machine	❌ Never	✅ Sent to API	✅ Sent to OpenAI
Credentials visible in screenshots	Your risk to manage	Anthropic sees them	OpenAI sees them
Data retention	None (local)	Per API data policy	Per OpenAI policy
GDPR compliance	✅ Trivial (no data transfer)	Requires DPA	Requires DPA
Audit trail	You control it	API logs	No access

For enterprise use: Fara-7B is the clear winner for privacy. No screenshots of internal tools, customer data, or credentials ever leave your infrastructure.

When to use each

Use Fara-7B when:

• Privacy is critical (internal tools, customer data, credentials)
• You need to run thousands of tasks per day (cost)
• You want to customize/fine-tune for your specific UI
• You’re building a product that embeds computer use
• You’re in a regulated industry (healthcare, finance, government)

Use Anthropic Computer Use when:

• You need the highest accuracy on complex tasks
• Tasks require deep reasoning or judgment calls
• You’re prototyping and don’t want to manage infrastructure
• You need multi-tab, file upload, or drag-and-drop
• Budget isn’t the primary constraint

Use OpenAI Operator when:

• You’re a consumer wanting personal task automation
• You don’t need API access or custom integration
• You want the simplest setup (just use ChatGPT)
• Tasks are occasional, not high-volume

Can you combine them?

Yes — a smart approach is to route tasks based on complexity:

def choose_agent(task_complexity: str):
    if task_complexity == "simple":
        return "fara-7b"  # Free, fast, local
    elif task_complexity == "complex":
        return "anthropic"  # Best accuracy
    else:
        return "fara-7b"  # Default to free/private

Use Fara-7B for 90% of routine tasks (form filling, navigation, data entry) and fall back to Anthropic’s API for the 10% that require superior reasoning.

The bigger picture

Computer Use Agents are still early. Current limitations across all three:

• Fragile on dynamic UIs — Animations, popups, and CAPTCHAs break them
• No long-term memory — Each task starts fresh
• English-centric — Non-English sites have lower accuracy
• Safety concerns — An agent with browser access can do damage if misconfigured

But the trajectory is clear: within 12-18 months, these agents will handle most routine web tasks reliably. Fara-7B’s open-source release accelerates this — expect a wave of fine-tuned variants for specific industries and use cases.

FAQ

Can Fara-7B be as good as Anthropic Computer Use with fine-tuning?

For specific, narrow tasks (your company’s internal tools, a specific booking flow), yes. Fine-tuning on your exact UI can close the gap significantly. For general web browsing across arbitrary sites, the larger models still have an edge.

Is Operator going to get an API?

OpenAI hasn’t announced one. Currently Operator is consumer-only (ChatGPT interface). If you need programmatic access to computer use, Anthropic’s API or Fara-7B are your options.

Which is safest to let run unattended?

None of them should run fully unattended on sensitive tasks. All three can make mistakes. Fara-7B has the advantage of built-in critical points (pauses before purchases/logins), and since it’s local, a mistake doesn’t leak data to a third party.

Will Google release a competing model?

Likely. Google’s DeepMind has published research on web agents (WebAgent, SeeAct). A Gemini-based computer use agent is expected but hasn’t been released as of May 2026.

Related articles

• What is Microsoft Fara-7B?
• How to Run Fara-7B Locally
• Claude Computer Use Guide
• Best AI Coding Agents 2026
• How to Reduce LLM API Costs