Should I use a model router if I only need OpenAI today?

Usually: no, not at first.

If you only need OpenAI today, a model router is often unnecessary overhead. You can keep things simpler by integrating directly with OpenAI’s API and adding a small abstraction only when you actually need it.

Use a router later if you expect:

• Multi-provider support soon: OpenAI today, Anthropic/Gemini/local models tomorrow.
• Fallbacks/redundancy: e.g. switch providers if one is down or rate-limited.
• Cost/performance optimization: route easy tasks to cheaper models.
• Prompt/model experimentation: compare models without rewriting app code.
• Centralized policy controls: logging, guardrails, caching, rate limits.

Skip it for now if:

• You’re building an MVP.
• OpenAI is the only provider you’ll use for the foreseeable future.
• You want fewer dependencies and less debugging surface.
• You don’t need dynamic routing logic.

A good compromise

Create a thin provider interface in your own code, but implement only OpenAI at first. That gives you:

• easy migration later,
• minimal complexity now,
• no dependence on a full router until you need one.

If you want, I can sketch a simple “future-proof but not overengineered” architecture for this.