WEB LLaMA-65B and 70B: Unleashing Power, but at a Price

Optimizing Performance with GPUs

WEB LLaMA-65B and 70B, Google's latest language models, demand significant computational resources. To harness their full potential, a GPU with at least 40GB VRAM is recommended. For optimal performance, GPUs with over 48GB VRAM are required for 32k context processing, as 16k is the maximum that can be loaded on two 4090 GPUs with 24GB VRAM each.

Memory Requirements and System Specifications

Under FPBF16, a minimum of 128-129GB RAMVRAM is necessary to load the model. Building a system from scratch to meet these specifications could cost approximately 9K. This configuration would include a powerful 1000w PS, two A6000 GPUs with 96GB VRAM, 128gb DDR4 ram, and an AMD 5800X processor.

Addressing Efficiency Concerns

While these specifications ensure optimal performance, they also present challenges in terms of cost and efficiency. To resolve these issues, efforts are underway to improve training speed and reduce VRAM usage. This will ultimately enable faster training and lower compute costs for users of WEB LLaMA-65B and 70B.