How to choose the right LLM for your project

Choosing an LLM isn’t just about benchmarks. You need to match model size, context length, and cost to your use case.

Context length Long documents or codebases need 100K+ tokens. Claude and GPT-4 lead here. For short Q&A, 8K–32K is enough.

Cost Input/output pricing varies a lot. Estimate your monthly tokens and run the numbers. Often a smaller model with good prompting beats a large one for simple tasks.

Use case Coding: Claude and GPT-4. Search and citations: Perplexity. Writing and docs: ChatGPT, Claude, Notion AI. Pick one primary and one fallback.

API vs product APIs give flexibility; products (ChatGPT, Claude, etc.) give speed and UX. Start with a product, move to API when you need automation or integration.