Jamba (AI21)

AI21's hybrid Mamba + Transformer MoE model — 256k context window; open-weights. First production model with SSM-Transformer hybrid architecture.

At a glance

Optimised for: searched not found

Anti-fit: searched not found

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Jamba 1.5 Large/Mini open weights; 256k tokens.

Other recent method papers — theorized, no distinct product in the catalog, ranked by inbound references.

Compressive Transformer T3
Maintains recent states in full resolution while compressing older memories with learned compression functions. DeepMind.
MemGPT v2 / agent-tools T3
Already in catalog as the foundational MemGPT paper. Note: Letta is the productionised successor (cross-listed).
Transformer-XL T3
Extends context through segment-level recurrence + caching of hidden states from prior segments. Foundational long-context architecture.
Generative Agents T3
Park et al. — landmark agent-simulation paper. Reflection + memory stream + retrieval enable believable agent behavior.
MemoryBank T3
Enhances LLMs with long-term memory. Early influential paper.
Reflexion T3
Language agents with verbal reinforcement learning.