MDP Group’s Post

Accuracy isn’t enough, LLMs must also be fast. At MDP Group, we know that deploying LLMs in production is not only about accuracy. It’s about responsiveness. Users expect instant interactions, which means:  • Optimizing TTFT (Time To First Token), TPOT (Time Per Output Token), and P99 latency  • Tackling the KV cache memory wall that limits batch sizes and context windows  • Applying real optimizations: quantization, PagedAttention, FlashAttention, speculative decoding, prefix caching, and dynamic batching  • Benchmarking the entire pipeline (retrieval, prompt assembly, inference, post-processing), not just the model In her latest article, Rabia Eda Yılmaz from our MDP AI team shares how to design end-to-end pipelines for fast, reliable, and scalable LLM systems using chatbot experiences as the example. Blog link: https://lnkd.in/dMaJhDCc #MDPGroup #MDPAI #AI #EnterpriseArtificialIntelligence