AI Memory

AI memory allows models and agents to recall past interactions, adapt over time, and reason more effectively. We examined the most popular LLMs' ability to store information in both long-term and short-term memory, along with their context window capabilities.

AI Memory: Most Popular AI Models with the Best Memory

AI MemoryJan 28

Smarter models often have worse memory. We tested 26 large language models in a 32-message business conversation to determine which actually retain information. AI memory benchmark results We tested 26 popular large language models through a simulated 32-message business conversation with 43 questions.

AI MemoryJan 26

Best LLMs for Extended Context Windows in 2026

We ran a proprietary 32-message conversation test on 22 leading AI models to see how much of their advertised context windows actually work. The conversation includes synthesis tasks that require recalling information from earlier messages, not just parroting the last thing said.

AI MemoryNov 26

AI Apps with MCP Memory Benchmark & Tutorial in 2026

We tested memory tools to find out which ones actually work best for AI agents. Using LangChain’s ReAct Agent, we connected four different Model Context Protocol (MCP) memory servers and measured their performance in real scenarios. Beyond benchmarking, we built a working demo that connects Claude with Cursor through OpenMemory MCP.

AI MemoryNov 26

Cognitive Agents: Creating a Mind with LangChain in 2026

A cognitive agent isn’t just a chatbot responding on command; it’s a system that perceives, reasons, and adapts as its environment changes. AI agent memory capability helps AI agents to keep track of what’s happening now, what happened before, and which pieces of information are worth carrying forward. Without this, every conversation becomes a blank slate.