Understanding Large Language Models Series

Grouped Query Attention (GQA): Scaling Transformers for Long Contexts

January 27, 2026 by Nat Currier 11 min read

Excerpt

Discover how Grouped Query Attention became the secret weapon behind 1M+ token context windows in 2025's flagship models, enabling massive scaling without exploding memory costs.

Cite This

Nat Currier. "Grouped Query Attention (GQA): Scaling Transformers for Long Contexts." nat.io, 2026-01-27. https://nat.io/blog/grouped-query-attention-gqa-scaling-transformers

Grouped Query Attention (GQA) reduces memory in transformers by sharing key-value projections across query groups, enabling models like Llama 3.1 and GPT-4o to handle 1M+ token contexts efficiently.

https://nat.io/blog/grouped-query-attention-gqa-scaling-transformers

Key stat: 11 minute read