Unverified50% confidenceFactExact time
Even if the context window expands to millions of tokens, cross-session memory remains an engineering challenge, usually requiring an external vector database or a structured memory layer to achieve.
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50%
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Long-term
Relevance
10/13/2026
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Related Claims
VerifiedAn agent's memory includes short-term memory (conversational context window, typically 4K–128K tokens), long-term memory (vector database), and procedural memory (intermediate state cache for tool calls).78% similarUnverifiedShort-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 database77% similarUnverifiedThe conversational memory mechanism is essentially concatenating historical messages into the context window, so context length limits (e.g., 4K, 8K, 128K tokens) become a key constraint.77% similarUnverified业界应对长程记忆问题的方案包括外部记忆存储（如向量数据库）、结构化状态机管理和周期性上下文压缩摘要，但目前尚无完美解法76% similarUnverifiedWhen large models generate long texts, they need to cache the key-value pairs (KV Cache) of all previous tokens, and the memory footprint grows linearly with context length, making it very easy for this to become a memory bottleneck in high-concurrency scenarios.75% similar
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