New LLMs Slash Long-Context Memory Costs | dailyai.report
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Model
90d ago
New LLMs Slash Long-Context Memory Costs
KV sharing and compressed attention now drive efficiency in Gemma 4 and DeepSeek V4. These architectural shifts reduce the memory overhead required to process massive prompts. Developers can now deploy longer context windows on cheaper hardware.
The Signal
This trend prioritizes inference speed over raw parameter count for open-weight models.