How to evaluate and optimize LLM inference in a company
Andrew Chan’s article, published on March 1, 2026, covers fast LLM inference from scratch as a practical starting point for engineers.
Source: Inferência rápida de LLM do zero (andrewkchan.dev). Text prepared with AI from this source.
What happened and what to do
Andrew Chan’s article, published on March 1, 2026, covers how to implement fast language-model inference from scratch. Its scope is presented as a practical starting point for engineers; no specific results beyond that purpose are attributed to the article.
A company can turn this topic into an evaluation plan: measure latency, throughput, memory use, and cost for relevant models and workloads, then compare implementation options on its own infrastructure. Based on the findings, it can define adjustments and monitoring to meet operational requirements, without assuming a particular technique fits every case.
How the consultancy can help
Wendelmaques can assess inference requirements and available infrastructure, scope an implementation, and support its operation, including metrics and monitoring.
Next step
Send a short description of your inference use case and operational requirements to receive a scoped proposal.
Let's assess your project
I reply with scope and a proposal.