OpenRouter, Yotta Labs split LLM routing

This is really a portability-and-operations decision, not a pure feature shootout. The Reddit thread reads like a buyer's guide for infra teams, not a launch announcement ([discussion](https://www.reddit.com/r/MachineLearning/comments/1s3sneb/d_llm_api_aggregators_in_2026_openrouter_vs/)).

• –OpenRouter's docs back up the mature-default label: 300+ models, 60+ providers, OpenAI-compatible API, no markup on provider pricing, plus routing/fallback and spend controls ([pricing](https://openrouter.ai/pricing)).
• –OpenRouter does carry DeepSeek and Qwen, so the real issue is less raw availability than whether Chinese models feel first-class in the routing and catalog experience ([Qwen](https://openrouter.ai/qwen), [DeepSeek](https://openrouter.ai/provider/deepseek)).
• –Yotta Labs frames Model APIs as a unified aggregator inside a broader AI infra stack, which helps explain the post's newer-entrant, thinner-community read ([Model APIs](https://console.yottalabs.ai/models/model-apis), [homepage](https://www.yottalabs.ai/)).
• –Going direct still wins for one or two providers, but the hidden tax shows up fast once billing, rate limits, incident handling, and policy drift multiply.