Anthropic is leasing SpaceX's Colossus 1 supercluster
- https://www.youtube.com/watch?v=3pkz-Ie_k_c
- Original title: Anthropic just…wait what
Anthropic is leasing SpaceX's Colossus 1 supercluster (~300 MW, ~220k H100s) — despite years of mutual loathing with Elon — because they badly underestimated demand. Theo maps the compute/data/research triangle and explains why every recent Anthropic move makes sense through that lens.
Anthropic's compute crisis
- Dario admitted at Code with Claude that Anthropic planned for 10× yearly growth but Q1 annualized at ~80×. Recent product churn (trying to pull Claude Code from Pro, peak-hour throttling) was about freeing capacity, not extracting more revenue.
- Their compute is fragmented across Trainium, Google TPUs and Nvidia. Researchers want CUDA, so they push inference onto TPU/Tn to free GPU for training — but it still wasn't enough.
What this means for users
- Peak-hour limit reductions gone; Claude Code 5h limits doubled. Helps burst users; weekly cap unchanged so heavy daily users see little improvement.
- API tier limits massively raised, especially input tokens (Tier 1: 30k → much more; Tier 4: 2M → 10M).
- Theo's conspiracy: Azure-hosted Claude latency curves mirror Anthropic's own hosting too closely — likely passthrough, not real Azure inference. AWS and GCP numbers are independent and faster.
XAI ↔ Cursor deal
- Three pillars of an AI lab: research, data, compute.
- XAI: lots of compute (Colossus 1 was sitting idle because nobody uses Grok), no good code data, thin research.
- Cursor: best code-interaction data anywhere (every model's history through their editor), some research, no compute.
- Anthropic: world-class research and good data, no compute.
- OpenAI: has all three and is now coming to AWS, killing Anthropic's enterprise wedge — which is why Anthropic swallowed pride and took Elon's GPUs. SpaceX's $10B / $60B Cursor option is essentially "$10B for the data, or $60B for the company."
The "shift left" data trick
- Multi-turn corrections in chat sessions become RL training data by literally moving follow-up user messages "to the left" of the assistant turn — which is why one-shot agent behavior keeps improving. This is why Anthropic fights so dirty to keep its model histories out of competitors' hands (banning Windsurf, banning XAI through Cursor, the Chinese-distillation article).