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A Smaller Qwen3.8 Built by Pruning Layers

A Smaller Qwen3.8 Built by Pruning Layers

A community developer created Qwen3.8-23B-Mini-Me by strategically removing layers from Qwen3.8-27B, reducing the model to approximately 22.7B parameters without severe reasoning degradation. The model is reported to work well for coding, agentic tasks, and multi-turn chats, but it has not yet been benchmarked and struggles more with edge cases and underspecified prompts.

Reddit r/LocalLLaMACommunity1d ago#model-pruning#model-compression#apple-silicon
Scale Agentic AI Without Lock-In

Scale Agentic AI Without Lock-In

AWS outlines enterprise patterns for operating many agentic AI systems across diverse frameworks, models, and providers. The guidance focuses on preserving flexibility and enabling multi-agent systems to scale together without vendor lock-in.

AWS Machine Learning BlogOfficial10h ago#agentic-ai#multi-agent#vendor-lock-in
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