The Problem with Computer Use Agents
Computer use AI agents like Claude's Computer Use API are powerful, but they come with serious drawbacks when used for testing at scale:
- Expensive token costs - Every browser action requires thousands of tokens for screenshots and processing
- Brittle and unreliable - Small UI changes can break automated flows
- Poor at subjective tasks - Can't evaluate "does this feel right?" or catch UX issues
- Slow iteration - Each test run takes minutes and costs add up quickly
Human testers solve all of these problems. They're adaptable, intuitive, and cost a fraction of what you'd pay for computer use at scale.
Cost Comparison: Humans vs Computer Use
The following table shows the cost of running multi-step UI tests using Claude's Computer Use API vs real human testers.
Assumes 5.24 seconds per step for human testing (General Use tier at $0.0018/sec).
| Steps | Total Input Tokens | Total Output | Sonnet 4.5 | Opus 4.5 | Human Time | Human Cost |
|---|---|---|---|---|---|---|
| 5 | 28,190 | 500 | $0.09 | $0.15 | 26.2s | $0.047 |
| 10 | 96,705 | 1,000 | $0.31 | $0.51 | 52.4s | $0.094 |
| 15 | 213,045 | 1,500 | $0.66 | $1.10 | 78.6s | $0.142 |
| 20 | 377,210 | 2,000 | $1.16 | $1.94 | 104.8s | $0.189 |
| 25 | 589,200 | 2,500 | $1.81 | $3.03 | 131s | $0.236 |
| 30 | 848,965 | 3,000 | $2.59 | $4.32 | 157.2s | $0.283 |
Cost Growth Visualization
See how costs scale as test complexity increases
Key Insights
- Human testing costs 50-200x less than computer use agents
- Cost gap increases dramatically with test complexity
- At 30 steps: Opus costs $4.32 vs Human costs $0.175
- Human costs scale linearly, AI costs explode exponentially
Why Humans Win
- Adapt instantly to UI changes without retraining
- Catch subjective UX issues AI cannot detect
- No token costs for screenshots and processing
- Reliable results even with complex interactions
When to Use Human Testing
Perfect For
- E2E testing of critical user flows
- Visual regression testing
- UX/accessibility feedback
- Pre-deployment smoke tests
- Testing complex interactions
- Validating AI-generated code
Use Computer Use For
- Rapid prototyping (1-2 tests)
- Internal dev tooling
- Tasks requiring code execution
- When human judgment isn't needed
How RunHuman Works
Define Your Test
Send a test request via API with a URL, description, and JSON schema for results.
Human Executes Test
A trained human tester performs the task in their browser and describes what they see.
AI Extracts Results
GPT-4o converts the human's natural language response into structured JSON.
Get Results
Poll the API or use webhooks to get your test results in seconds.