On May 6, 2026, Anthropic announced a partnership with SpaceX to use all compute capacity at the Colossus 1 data center in Memphis, adding over 300 MW and 220,000+ Nvidia GPUs within a month. The deal lets Anthropic immediately double Claude Code’s five-hour rate limits, lift peak‑hour throttling for Pro/Max, and substantially raise Opus API rate limits.
This article aggregates reporting from 7 news sources. The TL;DR is AI-generated from original reporting. Race to AGI's analysis provides editorial context on implications for AGI development.
Anthropic’s move to lease all of Colossus 1 is one of the clearest signals yet that the race to AGI has entered the era of extreme‑scale compute alliances. By securing more than 220,000 Nvidia GPUs and 300 MW of dedicated capacity in a single facility, Anthropic is effectively adding another frontier‑class training cluster to its roster alongside massive commitments with Amazon, Google, Microsoft, Nvidia and Fluidstack. ([anthropic.com](https://www.anthropic.com/news/higher-limits-spacex)) This level of redundancy and headroom gives the company the freedom to run overlapping long‑horizon training runs, large safety experiments, and high‑throughput inference for Claude Pro/Max without the hard trade‑offs that recently forced aggressive rate caps.
Strategically, the partnership is remarkable because it turns a direct rival—Elon Musk’s xAI, now folded into SpaceX—into a landlord and infrastructure supplier. That suggests compute markets are tightening enough that ideology yields to utilization and cash flow. The kicker is Anthropic’s and SpaceX’s stated interest in multi‑gigawatt orbital AI compute, which, if realized, would decouple frontier training from terrestrial power and land constraints and push the scale frontier far beyond today’s hyperscale campuses. ([x.ai](https://x.ai/news/anthropic-compute-partnership)) For now, the immediate impact is pragmatic: doubled Claude Code limits, higher Opus API ceilings, and a stronger guarantee that Anthropic can keep pace with OpenAI and Google on model scale and availability.



