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2026 architecture research has moved beyond simply scaling transformers larger, branching into hybrid architectures, state space layers, MoE capacity allocation, activation behavior, and representation geometry.
Raschka observes that 2026 architecture innovation spans several new directions—hybrid designs, state space layers, MoE capacity routing, and more—rather than just building bigger transformers. ✦ AI generated
Sebastian Raschka · Ahead of AI · 2026-06-06 · original ↗
One thing I find interesting about 2026 so far is that architecture work goes beyond making transformers larger. There is a lot of work around hybrid architectures (for example, Nemotron 3, and Arcee Trinity), state space layers (Nemotron 3 and Mamba-3), MoE capacity allocation (Scaling Embeddings Outperforms Scaling Experts, and Step 3.5 Flash).
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In practice · 2
Nemotron 3 alternates regular attention layers with Mamba-2 state-space layers to improve long-context efficiency, which has become the central priority in 2026 as more LLMs get embedded in agent harnesses requiring longer contexts.Sebastian Raschka · Ahead of AI · conf 85%Qwen3.6, likely the most popular open-weight LLM series using a hybrid design, substitutes Gated DeltaNet layers for Mamba-2 in its non-attention portions.Sebastian Raschka · Ahead of AI · conf 80%