Unverified50% confidenceFactExact time
Tesla on the one hand purchases Nvidia GPUs to build clusters, and on the other hand develops its own Dojo supercomputer, seeking to use custom chips to lower training costs and reduce dependence on external suppliers.
1
Sources
50%
Confidence
Long-term
Relevance
10/21/2026
First Seen
Sources
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Related Claims
UnverifiedThe businesses of Tesla, xAI and SpaceX all require large numbers of processors, covering automotive chips, AI training and inference chips, and specialized processors for aerospace communications.73% similarUnverifiedTesla's Dojo uses a custom D1 chip integrating 50 billion transistors per chip, manufactured on TSMC's 7nm process, with 25 D1 chips forming one training module providing approximately 9 PetaFLOPS of computing power70% similarUnverifiedMeta's MTIA, Amazon's Trainium/Inferentia, and Tesla's Dojo are all examples of custom in-house chips developed by major companies for silicon-level customization of their own workloads70% similarUnverifiedTesla has already developed processors for vehicle systems, while AI workloads place completely different requirements on chip design.68% similarUnverifiedTesla Optimus、Figure、Physical Intelligence等头部公司都在大量投入自建遥操作数据管线67% similar
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