- Elon Musk’s Colossus 2 expands to nearly 2 gigawatts total capacity.
- Majority of the expansion involves over 555,000 NVIDIA GPUs.
- xAI’s move capitalizes on advanced AI computing capabilities.
Elon Musk confirmed that xAI’s Colossus 2 supercomputer, the first gigawatt-level training cluster, is now operational and set for an upgrade to 1.5 gigawatts by April 2026.
Colossus 2’s expansion boosts AI capabilities, potentially impacting NVIDIA stocks and related AI sectors, although no direct cryptocurrency market effects are observed.
Colossus 2 Achieves 2GW with 555,000 NVIDIA GPUs
Colossus 2, led by Elon Musk, achieved a benchmark expansion by acquiring a third building, dubbed “MACROHARDRR”, increasing its capacity to nearly 2 gigawatts. This included integrating more than 555,000 advanced NVIDIA GPUs.
Immediate implications involve substantial improvements in AI computing capabilities. “We are expanding Colossus to a total capacity of nearly 2 gigawatts, including the addition of 555,000 NVIDIA GPUs,” said Elon Musk, Founder & CEO of xAI. This advancement supports both xAI’s Grok AI training and the computational needs of Musk’s other ventures, potentially influencing AI-driven market sectors.
The market has recognized this milestone as a significant enhancement of AI capabilities. Notably, there have been no reported direct market impacts on cryptocurrencies, although the narrative may indirectly boost BTC and ETH due to increased AI demand.
xAI’s Expansion Fuels Tech Industry Integration
Did you know? The original Colossus launched in 2024, becoming the world’s largest AI supercomputer with 100,000 H100 GPUs, setting a precedent for rapid AI compute scaling.
As per CoinMarketCap, Bitcoin (BTC) currently trades at $95,225.38 with a market cap of $1.90 trillion. Over the past 24 hours, its value decreased by 0.20%, while it gained 5.12% over a week. Market dominance is at 58.98%.
The Coincu research team highlights that this expansion could signal further vertical integrations in tech industries. xAI’s investment in self-sustaining power solutions may represent a model for future high-capacity computing expansions.
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