Decoupled DiLoCo: A new frontier for resilient, distributed AI training

Decoupled DiLoCo enables distributed LLM training across distant data centers with reduced bandwidth and hardware resilience.

• •Uses decoupled compute 'islands' with asynchronous data flow to isolate hardware failures and maintain learning
• •Achieves 20+ times faster training than conventional methods using only 2-5 Gbps network bandwidth
• •Self-healing infrastructure that continues training despite hardware failures and reintegrates recovered nodes
• •Successfully trained 12 billion parameter Gemma 4 models across four U.S. regions
• •Supports mixed hardware generations (TPU v5p and v6e) in single training runs, extending hardware lifespan

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