Is it cheaper to run an open-source model locally than pay for an API?
The costs of running locally
Local models have no per-token charge, so the cost of each request is mostly electricity. The upfront price is the real issue. A machine with enough memory for a useful model can cost a significant sum, and it loses value as newer hardware arrives.
Smaller models run on cheaper machines but often answer less accurately. You may need to spend more time on prompts or checks to get results that match a larger hosted model.
The costs of paying for an API
Hosted APIs charge per token, usually with different rates for input and output. Light workloads can cost very little each month, which makes them attractive for testing. Costs climb quickly with long documents, many tool calls, or agents that run all day.
Rates change and vary by model, so check the current price list before doing the math.
- Local: hardware, power, maintenance, and setup time
- API: per-token fees that scale with usage
- Break-even depends on volume and the quality you need
A simple way to compare
Estimate your monthly token volume for a typical task, multiply by the provider's rate, and compare that figure with the monthly cost of owning the hardware. Include the hours you will spend on upkeep. The option that wins at your volume is the cheaper one for you. Keep the numbers in a simple table so you can update them as prices change.
Common mistakes
- Counting only the hardware price and forgetting electricity and maintenance time.
- Comparing a small local model with a top hosted model and assuming the results are equal.
