A Practical Framework for Evaluating LLM Vendors

Every few months, a new model claims to beat the incumbents on some benchmark, and clients ask us whether they should switch. The honest answer is almost always "it depends on your workload," which is unsatisfying but true. Benchmark leaderboards rarely reflect the specific mix of tasks a given product actually needs.

Build an Evaluation Set From Your Own Data, Not a Public Benchmark

The single most useful thing a team can do before comparing vendors is assemble fifty to a hundred real examples from their own product — actual user queries, actual documents, actual edge cases — with a clear definition of what a good answer looks like for each. Public benchmarks measure general capability; your evaluation set measures whether a model is good at your problem, which is a different and much more useful question.

Cost and Latency Matter as Much as Raw Quality

A model that is marginally more accurate but noticeably more expensive or slower is often the wrong choice once you account for real usage volume. We ask clients to model out cost per request at their expected scale, not just at pilot volume, since pricing that looks trivial at low volume can become a meaningful budget line once usage grows. Latency matters just as much for anything user-facing — a slightly less accurate model that responds in half the time is frequently the better product decision.

Consider Operational Factors, Not Just the Model Itself

Rate limits, regional availability, data retention policies, and how quickly a provider ships breaking API changes all affect how painful it is to actually run a vendor in production. We have seen teams choose a technically excellent model and then spend weeks fighting rate limits during a traffic spike, or discover late that a provider's data handling terms do not satisfy a customer's procurement requirements. These operational details rarely show up in a marketing comparison but consistently show up in an incident channel.

Avoid Single-Vendor Lock-In Where It Is Cheap to Do So

Where the abstraction cost is low, we recommend building a thin interface layer that makes swapping providers a configuration change rather than a rewrite. This does not mean chasing every new release, but it means that when a genuinely better or cheaper option appears, or when a provider has an extended outage, switching is a days-long project instead of a months-long one.

Vendor evaluation is ultimately a product decision as much as a technical one. The teams that get the best results are the ones that measure against their own workload and their own constraints, rather than outsourcing the decision to whichever leaderboard is trending that month.