Unverified50% confidenceFactExact time
A context length of 131,072, i.e., 128K tokens, leads to significantly higher VRAM consumption and latency during inference as the context grows longer.
1
Sources
50%
Confidence
Long-term
Relevance
10/9/2026
First Seen
Sources
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Related Claims
UnverifiedShort-term working memory, i.e., the context window, is typically 8K to 128K tokens, while long-term memory is usually stored in the form of a vector database72% similarUnverifiedWhen the context expands from 4K tokens to 128K tokens (a 32× increase), the theoretical computation grows by approximately 1024×.71% similarUnverifiedHigher memory bandwidth means lower time to first token (TTFT) and higher tokens per second (TPS) generation.70% similarUnverifiedExpanding the context from 8K tokens to 1M tokens theoretically increases computational load by approximately 15,000 times.70% similarUnverifiedIn actual testing, the prefill read speed for a 32K context reached 3,860 tokens per second.70% similar
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