Together AI Revolutionizes Long-Context LLM Serving with Cache-Aware Architecture
research#llm📝 Blog|Analyzed: Feb 11, 2026 18:17•
Published: Feb 11, 2026 00:00
•1 min read
•Together AIAnalysis
Together AI has developed a groundbreaking cache-aware disaggregated inference architecture that dramatically improves the performance of serving long prompts to Generative AI models. This innovative approach, separating cold and warm workloads, offers a significant leap in efficiency and responsiveness for AI applications. The result is faster time-to-first-token and increased throughput, promising a better user experience.
Key Takeaways
- •CPD (cache-aware prefill–decode disaggregation) architecture boosts throughput by up to 40%.
- •The innovation focuses on efficient handling of 'warm' and 'cold' requests to optimize context reuse.
- •This advancement significantly lowers the Time-To-First-Token (TTFT) for better user experience.
Reference / Citation
View Original"By isolating heavy prefills and leveraging distributed KV cache, CPD delivers up to 40% higher sustainable throughput and significantly lower time-to-first-token (TTFT) for long-context inference — especially under mixed, real-world traffic."