AML Benchmark for Agent Memory Released: MemoraX Tops, NetEase Third
机器之心 · wechat · 2026-08-14
The inaugural Agent Memory Leaderboard (AML), co-launched by nearly 30 institutions including Oxford and Tsinghua, has been released to establish a unified evaluation standard for Agent long-term memory systems.
Key Leaderboard Insights
- Industrial Track: MemoraX dominates with a score of 58.0, ranking first across all 7 text memory dimensions. MemOS takes second place, while NetEase's NTES-MEMORY-SMART emerges as a dark horse in third, showing exceptional personalization capabilities.
- Open-Source Track: InvMem, ReFind, and ActiveMemoryIndex take the top three spots, representing distinct technical approaches like hybrid retrieval, iterative search, and fine-grained query rewriting.
Evaluation Mechanism
AML strictly isolates memory interfaces from generation, integrates over 10 benchmark datasets, and employs a multi-agent judging system to ensure fairness. This release marks the transition of the Agent memory track towards standardized evaluation.
Related event: First Agent Memory Leaderboard Released, MemoraX Tops(3 posts)→
More from coding & agent
- OpenAI researcher's 'how I react to most Codex outputs' meme nails the agent-review experience — alejandroll10 · 2026-10-16
- Sakana AI ships Agentic Scientist, orchestrating coding agents for automated scientific discovery — hardmaru · 2026-10-16
- One trailing dot bypassed VS Copilot's path check, enabling RCE (CVE-2026-103572) — wunderwuzzi23 · 2026-10-16
- Celestine MCP server adds astrology charts and transits to AI agents — modelcontextprotocol · 2026-10-16
- ProfitPlay MCP Server lets AI agents trade crypto and stock prediction markets — modelcontextprotocol · 2026-10-16
- Polyhaven flagged as a go-to resource for agents building realistic 3D scenes — jason_mayes · 2026-10-16