GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding
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- Authors credited
- Dehao Chen · Noam Shazeer · Yanping Huang · Zhifeng Chen
- Dates
- Published 2020-06-30 authorship evidence authorship evidence authorship evidence authorship evidence
- Exact source
- GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding arXiv · published 2020-06-30 · arXiv abstract page, retrieved for the candidate pack on 2026-10-28 (SHA-256 58afff7650a3cbdeb118df2dbfb58e3af85720ed2e54cc795c3a611c7cf3ea39). Submission history as arXiv records it (UTC): v1 30 June 2020. The page serves the latest version; each version is a separate expression, and only the one a record names was read.
- GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding arXiv · published 2020-06-30 · arXiv:2006.16668v1, submitted 30 June 2020 (UTC). Retrieved for the candidate pack on 2026-10-28 (SHA-256 4078d81e9ef6db2e3a982e56d3d8816766d8d49f350e02f7410501ca496ad54e). The author list is the byline as printed on the first page.
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Issue and authorship records
- Author: Dehao ChenDehao Chen is a credited author of GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.2020-06-30 · publication · Stated in source · Supported Inspect claim & evidence ↗Dehao Chen: person page →
- Author: Noam ShazeerNoam Shazeer is a credited author of GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.2020-06-30 · publication · Stated in source · Supported Inspect claim & evidence ↗Noam Shazeer: person page →
- Author: Yanping HuangYanping Huang is a credited author of GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.2020-06-30 · publication · Stated in source · Supported Inspect claim & evidence ↗Yanping Huang: person page →
- Author: Zhifeng ChenZhifeng Chen is a credited author of GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.2020-06-30 · publication · Stated in source · Supported Inspect claim & evidence ↗Zhifeng Chen: person page →
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Cited by · 5
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- Qwen Technical ReportQwen Technical Report cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.2023-09-28 · publication · Stated in source · Supported Inspect claim & evidence ↗Qwen Technical Report: document page →
- DeepSeek-V3 Technical ReportDeepSeek-V3 Technical Report cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.2024-12-27 · publication · Stated in source · Supported Inspect claim & evidence ↗DeepSeek-V3 Technical Report: document page →
- Kimi K2: Open Agentic IntelligenceKimi K2: Open Agentic Intelligence cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.2025-07-28 · publication · Stated in source · Supported Inspect claim & evidence ↗Kimi K2: Open Agentic Intelligence: document page →
- ERNIE 5.0 Technical ReportERNIE 5.0 Technical Report cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.2026-02-04 · publication · Stated in source · Supported Inspect claim & evidence ↗ERNIE 5.0 Technical Report: document page →
- Kimi K3: Open Frontier IntelligenceKimi K3: Open Frontier Intelligence cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.2026-07-28 · publication · Stated in source · Supported Inspect claim & evidence ↗Kimi K3: Open Frontier Intelligence: document page →
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What the document says it adds
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- In its own wordsThe paper presents GShard, described as a module of lightweight annotation APIs and an extension to the XLA compiler.“GShard is a module composed of a set of lightweight annotation APIs and an extension to the XLA compiler.” arXiv v1, PDF p. 1, abstract2020-06-30 · publication · Stated in source · Supported Inspect claim & evidence ↗
- In its own wordsThe paper reports using GShard's automatic sharding to scale a multilingual neural machine translation Transformer with Sparsely-Gated Mixture-of-Experts beyond 600 billion parameters.“GShard enabled us to scale up multilingual neural machine translation Transformer model with Sparsely-Gated Mixture-of-Experts beyond 600 billion parameters using automatic sharding.” arXiv v1, PDF p. 1, abstract2020-06-30 · publication · Stated in source · Supported Inspect claim & evidence ↗