Evaluating Long-Term Memory for AI Agents: AML Cycle 2 Is Now Open

The Agent Memory Leaderboard opened Cycle 2 of the Agent Memory Challenge 2026 on September 20, offering over USD 22,000 in prizes to eligible open-source teams. The challenge evaluates long-term agent memory across three tracks — Textual, Coding, and Multimodal — using a shared Add/Search interface and standardized Answer/Eval scoring to test whether agents retrieve current, useful evidence rather than stale context. Both open-source methods and commercial products can compete, with public, comparable results published at agentmemoryleaderboard.ai/evaluation.

Agent Memory Leaderboard on X: "Agent Memory Challenge 2026 Cycle 2 is now open. Long-term memory is not just about storing more history. It is about retrieving the right evidence, recognizing what has changed, and avoiding stale context when an agent needs to act. Three tracks: Textual · Cod… / X Agent Memory Leaderboard on X: "Agent Memory Challenge 2026 Cycle 2 is now open. Long-term memory is not just about storing more history. It is about retrieving the right evidence, recognizing what has changed, and avoiding stale context when an agent needs to act. Three tracks: Textual · Coding · Multimodal Open-source Methods · Commercial Products Over USD 22,000 prize pool for eligible open-source teams. A shared Add/Search interface. Standardized Answer/Eval. Public, comparable results. Join: https://t.co/t2QajOb7Fe" Agent Memory Challenge 2026 Cycle 2 is now open. Long-term memory is not just about storing more history. It is about retrieving the right evidence, recognizing what has changed, and avoiding stale context when an agent needs to act. Three tracks: Textual · Coding · Multimodal Open-source Methods · Commercial Products Over USD 22,000 prize pool for eligible open-source teams. A shared Add/Search interface. Standardized Answer/Eval. Public, comparable results. Join: agentmemoryleaderboard.ai/evaluation Agent Memory Challenge 2026 Cycle 2 is now open. Long-term memory is not just about storing more history. It is about retrieving the right evidence, recognizing what has changed, and avoiding stale context when an agent needs to act. Three tracks: Textual · Coding · Multimodal Open-source Methods · Commercial Products Over USD 22,000 prize pool for eligible open-source teams. A shared Add/Search interface. Standardized Answer/Eval. Public, comparable results. Join: agentmemoryleaderboard.ai/evaluation For the full technical overview of Cycle 2—including the shared Add/Search evaluation boundary, Textual, Coding, and Multimodal tracks, and the principles behind reproducible Agent Memory evaluation: Agent Memory Challenge 2026 Cycle 2 opens September 20. A shared evaluation for long-term Agent Memory across Textual, Coding, and Multimodal tracks—testing not just what agents store, but whether they retrieve current, useful evidence when it matters.