Fireworks introduces Multi-LoRA, an innovative capability within its FireOptimizer platform, designed to enable cost-effective personalization of AI models at scale. By allowing companies to serve hundreds of fine-tuned Low-Rank Adaptation (LoRA) models on a single base model simultaneously, Multi-LoRA offers a cost efficiency of 100 times compared to traditional methods, with inference costs as low as $0.2 per million tokens on Fireworks Serverless. This approach significantly enhances the ability to tailor experiences for diverse user segments without prohibitive expenses, making it particularly advantageous for companies serving large customer bases. Multi-LoRA also supports accelerated experimentation by allowing teams to work in parallel on multiple fine-tuned models, streamlining the process of combining successful experiments. Additionally, Fireworks provides flexible deployment options, including serverless, on-demand, and enterprise reserved, to suit different workload demands, while optimizing GPU utilization through techniques like Cross-Model Continuous Batching and Dynamic Loading.