What does this workflow do?
Retrieval-augmented generation (RAG) supplies retrieved evidence to a model before it generates an answer. A successful response must use relevant evidence and represent it faithfully.
o10Reviewed 2026-09-06
RAG Summarization inference
Retrieval-augmented generation (RAG) supplies retrieved evidence to a model before it generates an answer. A successful response must use relevant evidence and represent it faithfully.
Workload design guide. Any example volumes or cost estimates below are illustrative, not measured customer results.
SummaryKey takeaways
What you need to know
Start with the core questions, then examine the examples and tradeoffs below.
01Deep dive
Design the workflow before choosing a model
Evaluate retrieval separately from generation. Record the query, retrieved document IDs, document versions, selected passages, and final answer so a failure can be traced to the right stage.
Define a representative input and an explicit acceptance criterion. Keep model and prompt versions with the result so quality changes can be investigated.
02Deep dive
Evaluate outcomes and failure modes
Measure retrieval recall, answer faithfulness, citation accuracy, and appropriate abstention.
Test missing evidence, stale documents, near-duplicate passages, and conflicting sources. A fluent answer is insufficient if its claims are unsupported by the retrieved material.
Compare candidate routes on the same held-out examples. Report how many examples were evaluated and inspect failures rather than relying on a single average score.
03Deep dive
Roll out with a measurable cost baseline
First tune retrieval and context selection. Compare models on the same retrieved evidence before attributing a quality change to the generator.
Calculate cost per accepted outcome using input and output tokens, retrieval or tool fees, retries, and review effort. A lower token price is useful only if the total workflow still meets its requirements.
o10 can provide model routing for the inference steps. Your application remains responsible for workflow permissions, tool behavior, and deciding whether the final result is acceptable.
SourceMethodology
Measure performance and total cost on representative tasks before rolling out this workflow.
FAQFrequently asked questions
Common questions
What should be measured before changing the route?
Record the current workflow’s outcome quality, latency distribution, failure rate, and fully loaded cost. Compare the candidate on the same tasks and include failed attempts and retries.
Are the savings figures on this site guaranteed?
No. Calculator inputs and workload examples are illustrative. Establish your own baseline and measure the candidate under comparable conditions before projecting savings.
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See what you're overpaying →verified savings methodology · State of Inference Spend 2026