Unverified70% confidenceFactExact time
ZeRO was proposed by the DeepSpeed team in 2020 and eliminates redundancy in data parallelism through three stages: ZeRO-1 shards optimizer states, ZeRO-2 shards gradients, and ZeRO-3 shards model parameters.
2
Sources
70%
Confidence
Long-term
Relevance
7/14/2026
First Seen
Sources
JAX主机卸载技术：突破LLM训练显存瓶颈的实战指南
Related Claims
Unverified微软DeepSpeed提出的ZeRO技术分为三个阶段：Stage-1分片优化器状态可将内存需求降低约4倍，Stage-2额外分片梯度，Stage-3进一步分片模型参数79% similarUnverifiedDeepSpeed's ZeRO optimizer can reduce the GPU memory required per device to 1/N of the original by sharding optimizer states, gradients, and model parameters.72% similarUnverifiedZeRO-Infinity可将分片数据溢出至CPU内存乃至NVMe SSD63% similarUnverifiedZed added Grok 4.7 to the SuperGrok and xAI providers and set it as the recommended default model.60% similarUnverifiedZed released the v1.18.0-pre preview version, bringing improvements to AI model support, debugger functionality, Git integration, and cross-platform stability.57% similar
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