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MLOps Cost Per Model Calculator

Work out mlops cost per model instantly with clear inputs, formula shown and shareable results.

About MLOps Cost Per Model Calculator

Fully loaded cost per model is per-model training and serving plus an allocated share of the shared platform: feature store, registry, orchestration, monitoring and the team maintaining them. The platform share is what makes the first few models look absurdly expensive and the twentieth look cheap, and it is the honest number to compare against each model's business value.

Formula

Cost allocation

total = models x (training + serving) + platform; per model = total / models

Worked example

With the default values below, MLOps Cost Per Model Calculator returns Fully loaded cost per model per month of $3,050.00. Change any input above and every figure here is recalculated in your browser.

Inputs used

Models in productionminimum 1
12
Monthly training cost per modelminimum 0
800
Monthly serving cost per modelminimum 0
1,500
Shared platform cost per monthminimum 0
9,000

Results

Fully loaded cost per model per month
$3,050.00
Total monthly platform cost
$36,600.00
Share that is shared platform cost
24.59%
Annual cost
$439,200.00

Step by step

  1. 1Values used
  2. 2Cost allocation
  3. 3Fully loaded cost per model per month= 3,050.00
  4. 4Total monthly platform cost= 36,600.00
  5. 5Share that is shared platform cost= 24.59
  6. 6Annual cost= 439,200.00

Assumptions and limits

  • The result is derived only from the 4 inputs listed above. Anything not among them is not part of the calculation.
  • In particular, this calculator does not take inflation, tax or compounding frequency into account.
  • Figures are rounded for display to 2 decimal places, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.

How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.

Frequently Asked Questions

Should platform cost really be allocated per model?

For decisions about retiring or adding models, marginal cost is the right figure. For portfolio-level reporting, fully loaded cost prevents the platform from looking free.

What usually dominates the bill?

Serving, because it runs continuously, and idle endpoints in particular. Consolidating low-traffic models onto shared multi-model endpoints is normally the biggest saving available.

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