Hybrid Latent Attention for Looped Language Models

Name: Hybrid Latent Attention for Looped Language Models
Uploaded: 2026-10-20T15:28:02.903492+00:00
Duration: 275 s
Description: Looped language models reuse the same layers T times, which multiplies their KV cache and limits how many sequences a GPU can decode. Hybrid Latent Attention stores recent tokens exactly and older ones as compact latents read directly by each loop's query, shrinking the cache 10.7x, boosting throughput up to 7.4x, and keeping over 96% of accuracy.

Looped language models reuse the same layers T times, which multiplies their KV cache and limits how many sequences a GPU can decode. Hybrid Latent Attention stores recent tokens exactly and older ones as compact latents read directly by each loop's query, shrinking the cache 10.7x, boosting throughput up to 7.4x, and keeping over 96% of accuracy.

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