How do you reduce LLM API costs?

On $6,000 a month of model spend with 56% of it in two workflows, those two cost $40,320 a year. Moving them to smaller models at a 60% cost cut saves $24,192 a year and brings the monthly bill to $3,984. Top-two spend per year = monthly spend × 12 × share in the two biggest workflows. Saved per year = top-two spend × cost cut. Monthly spend after = monthly spend − monthly spend × share × cost cut.

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How much of your AI model spend can you cut?

On $6,000 a month of model spend with 56% of it in two workflows, those two cost $40,320 a year. Moving them to smaller models at a 60% cost cut saves $24,192 a year and brings the monthly bill to $3,984.

Those are the defaults. Move the sliders to your own numbers.

Model spend per month $6,000Share of spend in your two biggest workflows 56%Cost cut from moving those to smaller models 60%

Spend in the top two, per year$40,320Where the money actually goes

Saved per year$24,192Top-two spend × the cost cut

Monthly spend after$3,984Everything else left alone

An estimate from your own inputs, not a quote or a guarantee. Your numbers stay in your browser until you send them.

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How the math works

Top-two spend per year = monthly spend × 12 × share in the two biggest workflows.
Saved per year = top-two spend × cost cut.
Monthly spend after = monthly spend − monthly spend × share × cost cut.

What it leaves out

The eval work that proves the smaller model is good enough. That is the real job, and skipping it is how quality drops without anyone noticing.

About the defaults

56% is what we found in one audit of 157,000+ model calls a year: two workflows carried more than half the spend, and both moved to smaller models with no quality drop we could measure. The 60% cut is a planning number. The real one depends on which models you move between.

What we would do about it