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Anthropic ramps up Claude's capabilities with expanded usage limits and a major deal with SpaceX to harness Colossus 1’s full power, alongside support from tech giants Amazon, Google, and Microsoft.
Anthropic, the AI research lab behind Claude, is significantly enhancing its usage limits for both Claude Code and Claude Opus models. Starting today, many Claude Code users will see their five-hour rate limits doubled, the peak hours limit reduction removed, and API rate limits for Claude Opus models substantially increased. These improvements are powered by a new deal with SpaceX to leverage all of the compute capacity at their Colossus 1 data center in Memphis. Anthropics also cites recent partnerships with Amazon, Google, and Microsoft as contributing factors.
The boost in compute resources is a major win for developers and organizations using Claude. For context, Claude Code is designed for complex coding tasks, while Claude Opus models are tailored for cybersecurity applications. Both have been constrained by rate limits that often hindered productivity during peak usage hours. The new changes should alleviate these bottlenecks and enable more consistent performance.
The deal with SpaceX to utilize the Colossus 1 data center is a significant milestone. Here's what it entails:
In addition to SpaceX, Anthropics has secured deals with other tech giants:

These partnerships collectively provide a robust infrastructure that supports Anthropics' ambitious goals for Claude.
The enhanced usage limits and increased compute resources will have several practical implications:
However, there are also some considerations to keep in mind:
Overall, these changes represent a significant step forward for Claude and highlight Anthropics' commitment to providing powerful AI tools that meet the evolving needs of its user base.
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Anthropic’s Claude usage limits are getting a boost after compute deals with SpaceX and others.
↗ https://www.theverge.com/ai-artificial-intelligence/925348/anthropics-claude-usage-limits-are-getting-a-boost-after-compute-deals-with-spacex-and-others
About the author
Kai built ML infrastructure at a Bay Area startup before developing an obsession with transformer architectures and inference optimisation that eventually pulled him out of product work entirely. A stint at a compute research lab sharpened his instinct for what actually matters in a model release versus what is marketing. He writes from the inside — from the perspective of someone who has debugged the systems he is describing at three in the morning. He is allergic to hype and instinctively drawn to the unglamorous plumbing questions that everyone else skips over.
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