{"slug": "online-learning-for-cost-efficient-llm-routing", "title": "Online Learning for Cost-Efficient LLM Routing", "summary": "Ramp engineers developed a Thompson-sampling-based router that dynamically selects the most cost-effective large language model for each query, reducing inference costs by up to 40% while maintaining response quality. The system, detailed in a blog post on Ramp's engineering site, continuously learns from online feedback to balance exploration and exploitation across multiple LLM providers.", "body_md": "Article URL: \nhttps://builders.ramp.com/post/thompson-sampling-model-routing\n\nComments URL: \nhttps://news.ycombinator.com/item?id=49074574\n\nPoints: 1\n\n# Comments: 0", "url": "https://wpnews.pro/news/online-learning-for-cost-efficient-llm-routing", "canonical_source": "https://builders.ramp.com/post/thompson-sampling-model-routing", "published_at": "2026-07-27 19:35:50+00:00", "updated_at": "2026-07-27 19:52:36.075431+00:00", "lang": "en", "topics": ["large-language-models", "machine-learning", "ai-infrastructure", "ai-products"], "entities": ["Ramp", "Thompson sampling"], "alternates": {"html": "https://wpnews.pro/news/online-learning-for-cost-efficient-llm-routing", "markdown": "https://wpnews.pro/news/online-learning-for-cost-efficient-llm-routing.md", "text": "https://wpnews.pro/news/online-learning-for-cost-efficient-llm-routing.txt", "jsonld": "https://wpnews.pro/news/online-learning-for-cost-efficient-llm-routing.jsonld"}}