Select-N introduces a groundbreaking memory offloading system for Large Language Models that balances cost efficiency with strict latency requirements.

• Reduces operational costs by supporting larger models, longer inputs, and bigger batch sizes
• Achieves 99.9% latency SLO compliance while maximizing memory utilization
• Delivers up to 34% cost reduction compared to traditional approaches
• Adapts dynamically to varying workloads and system constraints

This innovation enables organizations to deploy more powerful language models without compromising on performance guarantees or incurring unnecessary infrastructure costs.

Memory Offloading for Large Language Model Inference with Latency SLO Guarantees