Ultralytics

Ultralytics YOLO vs MMDetection ROI Calculator

Quantify the engineering cost of running a stagnant open-source detection framework. Plug in your team and see your savings in real dollars and recovered hours.

Your scenario

Tell us about your team

Total savings vs MMDetection
$0
Over 3 years · 0 hours of engineering reclaimed
Engineering hours saved
0
over the analysis horizon
Total dollars saved
$0
at your loaded engineer rate
Annual run-rate savings
$0
recurring after year 1
Per-engineer drag avoided
0 hrs
per engineer, per quarter
! Heads up

Risks the dollars don't capture

The numbers above only measure engineering time. The risks below shape committed deadlines and procurement conversations, but don't fit on a spreadsheet.

! Delivery risk

When a dependency breaks or an upstream server goes down, your release slips and there's no one to call. A maintained framework with commercial support gives you an accountable escalation path.

! Security & compliance

Unmaintained frameworks accumulate unpatched CVEs in their dependency tree, with no advisory feed and no remediation timeline. For any regulated workflow, that's an audit finding waiting to happen.

! Opportunity cost

Every hour fighting tooling is an hour not improving the model. Teams on a working framework run more experiments and ship better outcomes. Often the largest cost, and the hardest to see on a P&L.

Cost breakdown by category (engineering hours)

Where the difference comes from

Cost category Ultralytics MMDetection Hours saved $ saved
Total over horizon 0 hrs 0 hrs 0 hrs $0

Why the gap is real, not theoretical

MMDetection
Ultralytics
Adjust the underlying assumptions

The defaults below reflect what we hear from teams that have run both frameworks in production. Override any value to match your environment, and the model recalculates instantly.

Activity
Ultralytics
MMDetection
Unit

Migration risk is modeled as: probability of a forced migration during the horizon × hours to migrate per engineer. The default represents the per-engineer cost over a 3-year horizon. Total cost scales with team size and horizon length (a 5-year horizon implies near-certain migration).

Why these numbers are defensible: These numbers are based on real customer and user data. Every assumption above is editable so you can stress-test it against your own environment.