agentmemory V4 achieves 96.2% on LongMemEval benchmark, outperforms commercial AI memory systems

agentmemory V4 is an open-source memory system for AI agents that just achieved a world record score of 96.2% on LongMemEval, the standard benchmark for long-term AI agent memory.

Benchmark Performance

The system outperformed several funded AI memory companies:

• PwC Chronos: 95.6%
• Mastra: 94.87%
• OMEGA: 93.2% (raw)
• Supermemory: 85.86%
• Emergence AI: 86%
• Zep: 71.2%

Development Details

Built solo in 16 days on a mid-range gaming PC (i3-12100F) with a total cost of $1,000. The system uses Claude Opus as a generator and GPT-4o as a judge, but the retrieval architecture is the core innovation.

Technical Architecture

The system combines multiple retrieval techniques in a single SQLite-backed system:

• HNSW (Hierarchical Navigable Small World) for approximate nearest neighbor search
• BM25 for traditional text retrieval
• Cross-encoder for relevance scoring
• Knowledge graph integration
• Temporal grounding for time-aware memory retrieval

Availability

The system is open source under the MIT license and available at: github.com/JordanMcCann/agentmemory