How to Pick a GPU and Inference Engine for Large Language Models
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Dive into a comprehensive video tutorial on selecting the right GPU and inference engine for machine learning projects. Learn about the impact of quantization on model quality and speed, the relationship between GPU bandwidth and model size, and the effects of de-quantization on inference speed. Explore advanced topics like Marlin Kernels, AWQ, and Neural Magic. Compare popular inference software including vLLM, TGI, SGLang, and NIM, and discover how to deploy one-click templates for inference. Analyze detailed performance comparisons across various GPUs (A40, A6000, A100, H100) and model sizes (Llama 3.1 8B, 70B, 405B), including cost considerations. Gain insights into OpenAI GPT4 inference costs compared to Llama models. Conclude with valuable tips for optimizing inference setups and access additional resources for further learning.