#GPUoptimization

[ogeecircleman]

Artificial intelligence is advancing at an incredible pace, but we often stop to ask: what is the real limit? Is it just a matter of hardware power, or are there smarter ways to leverage current technology? DeepSeek has recently demonstrated that optimization can be more valuable than raw computing power, revolutionizing the way AI training is conducted.

The Game-Changer: 10 Times More Efficient than Meta

DeepSeek made waves by announcing that it trained its Mixture-of-Experts (MoE) model with 671 billion parameters in just two months, using a cluster of 2,048 Nvidia H800 GPUs. The result? A 10x efficiency boost compared to industry leaders like Meta. The secret behind this achievement was not just raw computing power but an innovative approach to GPU programming.

[innovatexblog]

🚀 GPU Cloud & Virtualization Just Got Smarter!

Looking to power up your AI and ML projects without breaking the bank? Our latest blog explores the top GPU-as-a-Service providers, shows you how to run TensorFlow on Google Cloud’s A2 instances, and reveals cost-saving tips using spot GPUs. Plus, we break down the true TCO of on-prem vs. cloud GPUs so you can make informed infrastructure decisions.

📊 Real benchmarks, hands-on walkthroughs, and cloud optimization insights—all in one place!

💡 Read now and level up your GPU strategy