llm routing systems - which decide which llm to use for what task - are getting more important, esp. if open source keeps flourishing yet there's no standard evaluation method for routing systems...enter ROUTERBENCH As the range of applications for Large Language Models (LLMs)

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Benchmarks & Metrics 🌐 #ROUTERBENCH: measures cost-efficiency and quality. 📊 Key metrics: 💰 Cost reduction: fewer calls to expensive models 📈 Quality retention: maintains 90% of GPT-4’s performance 🔄 Adaptability: dynamically optimizes thresholds for varying

1/n Optimizing the AI Ensemble: ROUTERBENCH Conducts the LLM Orchestra Imagine having a personal assistant that can handle any task you throw at it - from analyzing complex legalese to coding an app to writing creative stories. A super-intelligent aid that flexibly adapts its

Unlike traditional routing, which uses a single model for all inputs, token-level routing matches each token to the optimal model. On EmbeddLLM, deferral increased from 36% to 54% (+18 points). MixInstruct hit 84.2%, surpassing static bests. RouterBench achieved ~92% @SentientAGI

🎯 Our goal is to make RouterBench the ImageNet of LLM routing, setting a clear direction for the field and enabling faster progress. 🙌 Our code and dataset are open-sourced to facilitate the advancement of LLM routing research. 7/8 arXiv: https://t.co/LSyLBmibaK GitHub:

Empirically, CARROT performs better than state-of-the-art routers in popular datasets such as the Open LLM Leaderboard V2 and RouterBench. Moreover, CARROT can match (or even exceed) the best model performance at just a fraction of the cost. 4/6

RouterBench: A Novel Machine Learning Framework Designed to Systematically Assess the Efficacy of LLM Routing Systems https://t.co/mynuwpCRHx #ai #news #llm #ml #research

🚀 Introducing RouterBench, the first comprehensive benchmark for evaluating LLM routers! 🎉 A collaboration between @withmartian and Prof. @KurtKeutzer at @UCBerkeley, we've created the first holistic framework to assess LLM routing systems. 🧵1/8 To read more:

@johnrobb RouterBench: A Benchmark for Multi-LLM Routing System https://t.co/MCey76AZhL

#RouterBench: A Novel #MachineLearning Framework Designed to Systematically Assess the Efficacy of #LLM Routing Systems  #ML #LargeLanguageModel #dataset https://t.co/5pLQrkevLP

ROUTERBENCH: because who doesn't love a good router showdown? Surpassing, deteriorating rapidly and stretching into [0,infinity] - all in the name of LLMs. #AIQMetric #MLPandK https://t.co/3J715M8Zru

🚀 Introducing RouterBench, a groundbreaking benchmark for evaluating LLM routers! Developed by researchers at Martian, UC Berkeley, and UC San Diego, this framework offers a systematic approach to assess LLM routing systems. Dive into the details here:

@johnrobb Yeah was going to suggest Mixture of Experts (MoE) and multi-LLM routing as terms to investigate. There is a paper and github repo on the following ROUTERBENCH which might be a nice starting point to evaluate what you are thinking of. (next post)

RouterBench Magic 🌐: Ever wonder how your data gets from point A to B so smoothly? RouterBench is the new tool assessing AI routing systems' efficacy, ensuring your digital info travels on the best routes. #MachineLearning #DataRouting

1/3.🚀💡🤖 ROUTERBENCH ushers in a new era for LLM routing strategies https://t.co/ekEb8woA25 #LLM #ROUTERBENCH #AI #Benchmarking #Efficiency #CostEffectiveness #Innovation #DataDriven #LanguageModels #Technology @arxiv

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My Blog: Asus RT-N13U Wireless-N Internet Router – Benchmark Reviews: Asus RT-N13U Wireless-N Internet RouterBench... http://bit.ly/9EDH4A

The introduction of ROUTERBENCH will revolutionize LLM routing systems. It provides a much-needed standard for evaluation, helping to refine and optimize routing strategies for better performance and cost-efficiency.

Speed comparison: RouteLLM: ~50ms NVIDIA: ~20ms RouterBench: ~30ms 🚀 ARI: 12.3ms