Unverified60% confidenceFactExact time
The Mamba state space model was proposed by Albert Gu and Tri Dao in 2023, with both computational complexity and memory usage at O(1) during inference
2
Sources
60%
Confidence
Long-term
Relevance
7/10/2026
First Seen
Sources
GPT-5.6 Revealed: What a 54% Token Efficiency Boost in Agentic Coding Actually Means
hackernewshackernews7/9/2026
Related Claims
VerifiedState space models represented by Mamba compress historical information by maintaining a fixed-size hidden state, with both time and space complexity of O(1) during inference.77% similarVerifiedMamba 等基于状态空间模型（SSM）的架构以线性复杂度实现序列建模，更适合实时推理71% similarUnverifiedLinear-complexity models such as Mamba serve as a new architectural reference point targeting the O(n²) bottleneck69% similarUnverifiedIn 2023, Gu and Dao proposed Mamba, introducing an input-dependent selective scan mechanism that achieves language modeling performance comparable to or better than Transformers while maintaining linear time complexity.68% similarUnverifiedMamba2 maintains linear time complexity and constant state size, and therefore has a theoretical advantage in long-sequence scenarios.65% similar
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