Beyond Standard LLMs
Ahead of AI Sebastian Raschka, PhD
Alternative LLM architectures beyond standard transformer decoders are emerging, including linear attention hybrids, text diffusion models, and code world models. Notable examples include MiniMax-M1 and Qwen3-Next adopting Gated DeltaNet with linear attention scaling to improve efficiency from O(n²) to O(n) complexity, though MiniMax-M2 reverted to standard attention after encountering accuracy issues in reasoning tasks. These architectural experiments represent ongoing research into trade-offs between efficiency gains and performance maintenance in language model design.
Why it matters
Linear Attention Hybrids, Text Diffusion, Code World Models, and Small Recursive Transformers
