LLM Model Selection Consulting

The one that wins on your golden set under your cost, latency, and vendor-term constraints — often a different model per task. GPT, Claude, Gemini, and open weights are candidates, not a religion. LLM model selection consulting runs that bake-off in your cloud, pins the winner, and gates swaps. Four weeks is standard; financial-services review typically takes 8–12 weeks.

It depends on the task. Policy Q&A, coding, long-context review, and tool calling fail in different ways. We score each candidate on stratified cases with rubric judges, then add cost, latency, and contract terms. A model that wins a public coding leaderboard can still leak a retrieved document or ignore a tool schema. The bake-off is the answer.

When data residency, no-training requirements, cost at volume, or air-gapped serving beat a hosted API on the same evals. Open weights are not automatically safer or cheaper once you count GPUs and operators. We include a licensed open-weight candidate when those constraints exist, and we drop it when the golden set says quality does not hold.

They can veto a winner. If the use case includes data you cannot send to a model that trains on inputs, that provider is out for that traffic — regardless of quality. We score terms beside evals: training, retention, residency, subprocessors, and version pinning. Zero-retention on our side does not replace a bad vendor clause.

A default for low-stakes drafting can exist. High-stakes workflows should route by task and data class. One default is how a coding model becomes your legal Q&A engine. We design a small routing table with pins and a CI gate, not a mandate that every team use the same endpoint forever.

Pin versions where the provider allows it, sample live traffic, and run golden sets in CI on any swap. Rubric judges and reconstructable traces show which stratum broke. Online evals catch the update that arrived without a version bump. That is part of model selection, not a later observability project.

You pay the provider. We do not mark up tokens. The golden set, scorecards, traces, routing config, and IP are yours in your cloud. We operate zero-retention and do not use your cases for shared training. The process is SOC 2-aligned.

Four weeks is the standard bake-off: harvest cases, shortlist, score, route, handover. If you have no golden set yet, we build a thin one in that window rather than scoring on anecdotes. Financial-services selections with second-line review typically take 8–12 weeks. Rerunning the suite when a new model launches is a days-long exercise, not a new project.