Unverified50% confidenceFactExact time
Expanding the context window from 8K to 128K increases computational cost by 256 times.
1
Sources
50%
Confidence
Long-term
Relevance
9/8/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedThe context window of mainstream models has expanded from an initial 4K to 128K or even larger, but a larger context means higher inference latency and cost.75% similarUnverifiedTechniques such as Sliding Window Attention and RoPE positional encoding extension have expanded the context window from the early 2K tokens to 128K or even the million-token level.73% similarUnverifiedThe context window of modern large models has expanded from the early 4K tokens to 128K or even longer, and the computational complexity of the attention mechanism grows quadratically with context length.70% similarUnverifiedWhen models with hundreds of billions of parameters process a 128K context window, KV Cache can occupy tens of gigabytes of VRAM.69% similar
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