This blog post discusses the development and deployment of DigitalOcean's Inference Optimized Image for running large language models like Llama 3.3 more efficiently on GPUs. It highlights the significant performance improvements achieved through various optimizations such as speculative decoding, FP8 quantization, FlashAttention-3, and paged attention. The optimizations led to a 143% increase in throughput, a 40.7% reduction in time-to-first-token, and a dramatic 75% cost reduction per million tokens compared to traditional setups, demonstrating a more effective use of GPU resources.