Choosing an LLM for Your App: GPT vs Claude vs Open-Source Models

Picking a language model for a product isn’t just about which one scores highest on a benchmark. Here’s what actually matters in practice.

Closed models

Leading commercial models offer strong general reasoning, wide language and format support, and steady improvement without you managing any infrastructure. The tradeoff is per-token cost and dependency on a third-party API’s uptime and pricing changes.

Open-source models

Models you can self-host give you control over data residency and no per-token API cost once running. The tradeoff is you now own the infrastructure, and most open models trail the top closed models on complex reasoning.

What actually drives the decision

Data sensitivity, the complexity of the reasoning your product needs, expected volume and its effect on cost, and how much engineering capacity you have to manage self-hosted infrastructure.

A practical approach

Prototype with a closed-model API first since it’s the fastest way to validate whether your product idea works at all. Revisit the self-hosting question once you understand your real usage patterns and cost at scale.

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