Glossary
Inference cost optimisation
Reducing what AI features cost to run, usually 40 to 70% without measurable quality loss.
The levers are routing (use the cheapest adequate model per task), caching (semantic and exact), prompt compression, batching, and hard budget ceilings.
Every optimisation needs a before-and-after quality benchmark. A saving that quietly degrades output is a deferred cost, not a saving.
Start with measurement, not technique. A week of per-feature cost instrumentation usually shows that a small number of code paths account for most of the bill, and that at least one of them is calling a frontier model in a loop nobody intended. Fixing that is often the entire project.
Optimise in order of spend, not in order of interest. A week spent shaving tokens off a rarely-used feature is a week not spent on the one path that accounts for most of the bill, and cost instrumentation is what tells you which is which.
Related terms, in context
The concepts you almost always meet alongside inference cost optimisation.
- Token
- The unit models read and bill in, roughly three-quarters of an English word, and more for Indian scripts.
- Model routing
- Sending each request to the cheapest model that handles it adequately.
- Semantic caching
- Reusing a previous answer when a new question means the same thing, not just when it matches exactly.
Where this shows up in our work
Inference cost optimisation is not an abstraction for us. It is a decision we make on live projects. It shows up most directly in llm cost optimisation, where getting it wrong has a cost someone can measure.
If you are evaluating a vendor on this, the useful question is not whether they can define the term. It is what they measure, what they would refuse to do, and what happens in their system when the assumption behind inference cost optimisation stops holding.
Questions
What is Inference cost optimisation?
Reducing what AI features cost to run, usually 40 to 70% without measurable quality loss.
Does Orqent Labs build this?
Yes, LLM Cost Optimisation. We work across India, covering all 19,238 PIN codes remotely.
Building something that involves inference cost optimisation?
We will tell you honestly whether it is the right approach for your problem.
Or email bd@dtrasglobal.com · call +91 74118 77878