Unverified50% confidenceFactExact time
The context window refers to the upper limit of tokens a model can hold in a single inference, and it is the fundamental reason why agents' contexts are isolated in multi-agent systems and memory must be shared explicitly.
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50%
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Long-term
Relevance
11/1/2026
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Related Claims
UnverifiedA 1M token context window is different from a persistent memory mechanism; the context window is the total number of tokens the model can access in a single inference, and the content becomes invalid after the session ends or the window overflows, making it volatile state.78% similarVerifiedThe self-attention mechanism allows the model to dynamically weigh the importance of all other tokens in the sequence when processing each token, thereby capturing long-range semantic dependencies.77% similarUnverifiedOne of the core bottlenecks in multi-agent systems is not model capability itself, but information routing and memory management—that is, determining which portion of the parent thread each agent can see.76% similarUnverifiedBecause large model context windows are limited, long-horizon agents need to be designed with external memory mechanisms, encompassing three levels: short-term memory, long-term memory (vector database retrieval), and working memory.73% similarUnverifiedIn multi-agent systems, shared memory is held only by the orchestrator to achieve memory isolation and prevent incorrect facts from one agent from spreading and infecting all agents72% similar
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