How to Choose the Right Model

A systematic way to choose an LLM based on task type, quality requirements, latency, budget, context length, deployment, and compliance.

Selection dimensions

Evaluate task type, quality target, latency requirement, token budget, context needs, deployment environment, and data handling constraints.

Recommendations by task

Code generation often benefits from strong general or code models. Long document processing needs long-context models. Chinese scenarios can favor models optimized for Chinese. Sensitive environments may require local open-source deployment.

Cost-benefit analysis

High-budget systems can route core tasks to top models and cache repeated calls. Balanced systems use small models for simple tasks and larger models for complex tasks. Low-budget systems should prioritize routing, caching, batching, and efficient prompts.

Decision flow

Start with data constraints. If data cannot leave your environment, use local models. Then check context length, language, quality needs, and budget. Finally test candidates on your actual workload.