The optimization target shifted
Mamba-3 (March 2026, arXiv:2603.15569, ICLR 2026) marks an important shift in what the Mamba lineage is optimizing for. Mamba-1's headline was selectivity. Mamba-2's headline was training speed via SSD. Mamba-3's headline is inference: generate-time latency, throughput at long context, hardware utilization during decoding. As production deployments matured, deployment cost overtook training cost as the binding constraint, and Mamba-3 is the lineage's response to that shift.
Three concrete changes
Exponential-trapezoidal discretization. Earlier Mamba versions used zero-order-hold discretization, which is the simplest scheme but throws away information about how the input changes within a timestep. Exponential-trapezoidal uses both endpoints of the timestep, giving richer recurrence dynamics for the same number of operations. In practice this lets the model carry slightly more nuance per step.
Complex-valued states via RoPE. By representing the hidden state in complex space (effectively pairing dimensions and rotating them with RoPE-style angles), the state can encode phase information alongside magnitude. This improves state-tracking — the model's ability to maintain coherent counts and indices over long sequences — which is one of the historic weak points of pure SSMs.
MIMO formulation (Multiple-Input Multiple-Output). During autoregressive decoding, GPUs are dramatically underutilized — most of the time is spent waiting on memory accesses, with compute units idle. MIMO restructures the SSM to compute multiple outputs per step from multiple inputs, putting the otherwise-idle compute to work. Same wall-clock latency, more accuracy.
The numbers
At 1.5B scale, Mamba-3 SISO is the fastest model across all sequence lengths tested in the paper. MIMO adds about +1.8 accuracy points at comparable speed. None of these numbers will end the Transformer's reign, but together they explain why Mamba-3 is the version showing up in 2026 production hybrid work — it's the SSM variant where deployment economics actually pencil out.