Introducing Mockingbird: A High-Performance Generative Model for RAG
Get a view of the rigor put into making a generative LLM that enhances the performance of the entire RAG process
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Mockingbird LLM is here, and it is bringing unrivaled accuracy to RAG workloads. As part of the Vectara Trusted GenAI Platform, Mockingbird provides users with generative responses and structured outputs with levels of performance and accuracy that are ideal for running RAG workloads. Vectara platform users can now use the full solution without dependencies on third-party generative services. This makes Mockingbird not only the perfect choice for RAG performance but also versatile enough to be deployed across a multitude of form factors.
Join Sean Anderson (Head of Product Marketing) and Suleman Kazi (Software Engineer) as they explore several benchmarks that show the true power of the new model. You will get a view of the rigor put into making a generative LLM that enhances the performance of the entire RAG process with enhanced support for structured outputs and hallucination mitigation.
Explore a deep dive of Vectara's newest model that
Is specifically designed for Retrieval-Augmented Generation (RAG) and Structured Output use cases- Maintains low latency and cost efficiency
- Outperforms GPT4 and other major models in RAG output quality
