Model selection guide
The best AI model is the one that fits the system.
Model selection is an architecture decision. Quality matters—but so do cost, latency, privacy, context, reliability, and the workflow around the model.
Four useful model categories
01
Frontier models
Highest general capability
Complex reasoning, multimodal work, high-value copilots
Use when quality and adaptability matter more than unit cost.
02
Small models
Speed and efficiency
Classification, extraction, routing, high-volume tasks
Use for bounded tasks where latency and economics dominate.
03
Open-weight models
Control and portability
Private deployment, customization, regulated workloads
Use when infrastructure control or model ownership is strategic.
04
Specialist models
Domain precision
Vision, speech, embeddings, forecasting, document processing
Use when a narrow model outperforms a general one on a clear task.
Decision rule
Start with the workflow, define the evaluation, then earn the right to optimize.
A production system may route work across several models, deterministic rules, retrieval, tools, and human review. The model is one component of the operating design.