The most effective LLM cost optimization sequence is measure, right-size, reduce waste, route, and enforce. Optimize cost per successful task—not price per token—so a cheaper model that needs repeated retries does not look artificially efficient.
The INFRO view: INFRO puts routing, per-request cost estimation and one usage record in front of the providers you already pay, so optimization can happen with evidence instead of invoice archaeology.
Build a trustworthy baseline
Attribute every request to a model, route, project, environment, feature, input units, output units, and final outcome. Aggregate invoices are insufficient because they cannot tell you which product behavior created the spend.
Choose a business denominator: resolved ticket, generated report, completed agent task, or active customer. Cost per million tokens is a supplier metric; cost per outcome is a product metric.
Right-size the model
Run representative evaluations across premium, mid-tier, and efficient models. Move deterministic, high-volume work—classification, extraction, rewriting, moderation, and simple summaries—to the least expensive model that clears the quality threshold.
Reserve frontier reasoning for steps where its success rate changes the outcome. Many pipelines need one premium planning call, not premium tokens for every subtask.
Reduce avoidable tokens and media work
Trim repeated system text, retrieve fewer but better context chunks, cap output length, summarize conversation history, and avoid sending tool results the model no longer needs. For media, control duration, resolution, frame count, and unnecessary variants.
Cache only when correctness permits it. Exact-response caching works well for deterministic repeated prompts; semantic caching needs stricter review because similar language can hide different intent.
Route and enforce
Use routing to keep cost policy outside product code and budgets to prevent a broken loop, leaked key, or unexpected launch from consuming the month. Alerts should fire before a limit, while a hard ceiling contains the worst case.
Review unit economics after every model or prompt release. A five-percent output-length increase can matter more than a small list-price change at scale.
Where INFRO fits
Teams can compare supported models through one API, inspect per-request cost and latency, separate spend by project or key, and add controls as the organization grows. INFRO's public pricing tools and calculators make assumptions visible before traffic moves.
Start with a slice of real workload through the quickstart, compare cost per successful task, and confirm current early-access pricing and control availability rather than relying on a generic savings percentage.
Frequently asked questions
What is the fastest way to reduce LLM costs?
Measure by workload, then move high-volume tasks to the least expensive model that passes a representative evaluation. Model right-sizing often has a larger effect than prompt micro-optimizations.
Should I always choose the cheapest model?
No. Compare cost per successful task, including retries, validation failures, and human correction.
Does INFRO add a subscription fee?
INFRO charges a subscription for the control plane and takes no part of model spend; your providers invoice you directly for that. Verify current plans and early-access terms on the pricing page.
