New LLMs Slash Long-Context Memory Costs | dailyai.report
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Model
100d ago
New LLMs Slash Long-Context Memory Costs
KV sharing and compressed attention now power models like Gemma 4 and DeepSeek V4. These architectural shifts reduce the memory overhead required for massive context windows. By optimizing how keys and values are stored, developers can run longer prompts on cheaper hardware.
The Signal
This makes high-token processing viable for smaller, open-weight deployments.