Why I added a 6th LLM to my orchestrator (and why Grok with K is not Groq with Q)
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TL;DR: I built geo-orchestrator, an open-source multi-LLM pipeline in Python that routes tasks across 6 providers. Yesterday's real production run: 10 tasks, 5 waves, \$0.1967 total cost, 5/6 providers used, zero failures. Repo (MIT): The premise No single frontier model wins by itself anymore. Not Claude Opus 4.7. Not GPT-4o. Not Gemini 2.5 Pro. Not Grok 4.3. What wins is orchestration between them. I didn't reach this thesis by opinion. I reached it by running 1,189 calls with unified tracking.