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PaperLLMsv1.0

Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity

by Google Brain · open-source · Last verified 2026-03-17

Introduced Switch Transformers, a simplified mixture-of-experts (MoE) architecture that routes each token to exactly one expert (top-1 routing), enabling trillion-parameter models with sub-linear compute scaling. Switch Transformers achieve 7x pretraining speedup over a dense T5 model while maintaining model quality.

https://arxiv.org/abs/2101.03961
B+
B+Good
Adoption: AQuality: A+Freshness: B+Citations: AEngagement: F

Specifications

License
Apache 2.0
Pricing
open-source
Capabilities
sparse-computation, efficient-scaling, trillion-parameter-modeling
Integrations
Use Cases
efficient-pretraining, large-scale-nlp, model-scaling
API Available
No
Tags
mixture-of-experts, moe, sparse-model, scaling, efficiency
Added
2026-03-17
Completeness
100%

Index Score

75.8
Adoption
88
Quality
93
Freshness
71
Citations
88
Engagement
0

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