Nvidia\u2019s H100 chips<\/a> have become the industry standard for AI projects, due to their advanced processing capacity and performance. A single H100 chip can process around 900 gigabytes per second, making it perfect for large language models, which rely on processing billions, even trillions of parameters quickly, in order to provide fast, accurate AI responses. <\/p>\n No other chips have been found to perform as well for this task, which is why H100\u2019s are in high demand, higher than Nvidia itself can keep up with. And all the major AI projects are looking to stockpile as many as they can, but at a cost of around $30,000+ per unit, it\u2019s a major outlay for large-scale projects. <\/p>\n At present, xAI is running around 200k H100s within its Colossus data center in Memphis<\/a>, while it\u2019s also working on Colossus II<\/a> to expand on that capacity. OpenAI is also reportedly operating around 200k H100s<\/a>, while Meta is on track to blow them out of the water with its latest AI investments, which will take it up to around 600k H100 capacity<\/a>. \u00a0<\/p>\n Meta\u2019s systems aren\u2019t fully operational as yet, but in terms of compute, it does seem, at this stage, like Meta is leading the charge, while it\u2019s also planning to invest hundreds of billions more into its AI projects<\/a>. <\/p>\n Though there is another consideration within this, in additional custom chips that each company is working on to reduce reliance on Nvidia, and give themselves an advantage. All three, as well as Google, are developing their own hardware to power up their AI models, and because these are all internal projects, there\u2019s no knowing exactly how much they\u2019ll increase capacity, and enable greater efficiency on the back of their existing H100s.<\/p>\n So we don\u2019t know which company is going to win out in the AI compute race in the longer-term, but Musk has clearly stated his intention to eventually outmanoeuvre his opponents with xAI\u2019s strategy.<\/p>\n Maybe that\u2019ll work, and definitiely, xAI already has a reputation for expanding its projects at speed<\/a>. But that could also lead to setbacks, and on balance, I would assume that Meta is likely best placed to end up with the most capacity on this front. <\/p>\n Of course, capacity doesn\u2019t necessarily define the winner here, as each project will have to come up with valuable, innovative use cases, and establish partnerships to expand usage. So there is more to it, but from a pure capacity standpoint, this is how Elon hopes to power up his AI project. <\/p>\n We\u2019ll see if xAI is able to secure enough investment to keep on this path.<\/p>\n On another front, Elon has also outlined xAI\u2019s plans to open source all of xAI\u2019s models, with Grok 2.5 being launched on Hugging Face<\/a> over the weekend. <\/p>\n That means that anybody can view the weights and processes powering xAI\u2019s models, with Elon vowing to release every Grok model in this way.<\/p>\n
![\"Grok](\"https:\/\/www.newsbeep.com\/us\/wp-content\/uploads\/2025\/08\/Z3M6Ly9kaXZlc2l0ZS1zdG9yYWdlL2RpdmVpbWFnZS9lbG9uc19zdGFuY2UucG5n.webp.webp\"\/)
<\/p>\n