Before picking a platform, I think it's worth asking: why even bother with an aggregation layer?
For me, the pain point became obvious once I started juggling more than two model providers. Different API keys, different billing cycles, different request formats, and the constant context-switching between docs. If you're building anything that needs to switch between GPT for reasoning, Claude for coding, or a local model for cost-saving, a unified API is no longer a nice-to-have—it's a productivity multiplier. It abstracts away the boring plumbing so you can focus on what you're actually building.
OpenRouter — the established workhorse
Like many of you, I've used OpenRouter extensively. Its core value is clear: unmatched model breadth (300+ and counting), smart routing with fallbacks, and a massive community. It's the best discovery engine out there—want to test a newly released open-source model the day it drops? OpenRouter probably has it. The trade-off, which is transparently disclosed, is the platform fee baked into usage.
BasicRouter.ai — a newer alternative I'm exploring
Recently I stumbled upon BasicRouter.ai. Model count is smaller (around 50 curated ones), but it covers my daily stack—GPT, Claude, Gemini, DeepSeek, Qwen—and notably includes native image and video generation endpoints (Kling, Jimeng, Qwen-image) that OpenRouter doesn't focus on. Pricing is direct (no markup), and there's a small credit to test the waters. It feels like a pragmatic, "just the models I actually use" alternative.
**Curious what the rest of you are using to wrangle multiple models. **Sticking with direct provider APIs, or leaning on gateways? Let's hear it. 🦞
