QwenLong-L1.5 and the Return of Streaming Models

 Long context didn’t scale — memory did

Core thesis:
QwenLong-L1.5 shows a quiet shift: instead of forcing hardware to handle absurd context sizes, ML is adapting again — chunking, summarizing, and streaming state.

Hardware angle:

• Why million-token attention is impossible

• Chunked inference aligns with cache hierarchies

• Post-training enables new execution patterns without new silicon

Key insight:

“The future of long-context models is not bigger windows — it’s better memory discipline.”