NVIDIA introduces ReplaySSM, a state-storage method that speeds up decoding in hybrid SSM-attention models
Announced October 12, 2026
Verified (fact)
In a developer blog post, NVIDIA introduced ReplaySSM, a redesign of how state is stored to speed up decoding in hybrid models. Hybrid models mix a few attention layers in between state space model (SSM) layers. The post cites NVIDIA Nemotron 3, Qwen3.5 through Qwen3.8, Kimi-K3 and GLM-5.3-Flash as examples of hybrid models. The input materials do not confirm performance figures or whether the code has been released.
Needs fact-check (claim)
NVIDIA says the change in state storage makes decoding faster in hybrid models.
Why it matters (interpretation)
Major open models are moving to hybrid architectures, so SSM state management is becoming a new bottleneck and optimization target in inference serving.
Sources
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