Mamba: Linear-Time Sequence Modeling with Selective State Spaces
by Carnegie Mellon University / Together AI · free · Last verified 2026-03-17
Introduces Mamba, a selective state space model achieving Transformer-quality language modeling at linear time complexity. Its input-dependent state selection mechanism and hardware-aware algorithm enable efficient training and fast autoregressive inference without attention.
https://arxiv.org/abs/2312.00752 ↗B
B—Above Average
Adoption: B+Quality: A+Freshness: ACitations: BEngagement: F
Specifications
- License
- Apache 2.0
- Pricing
- free
- Capabilities
- sequence-modeling, linear-time-inference, selective-state-spaces
- Integrations
- huggingface-transformers
- Use Cases
- efficient-language-modeling, long-context-processing, real-time-inference
- API Available
- No
- Tags
- mamba, state-space-model, ssm, linear-time, selective, recurrence
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
63.8Adoption
72
Quality
90
Freshness
80
Citations
68
Engagement
0
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