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[ARTICLE · art-84805] src=verginglabs.com ↗ pub= topic=ai-agents verified=true sentiment=· neutral

A Markdown wiki outscored every AI agent memory product we benchmarked

A benchmark by an independent testing group found that a Markdown wiki outperformed every AI agent memory product tested, with Claude Code's built-in memory scoring 67.7% accuracy and costing $426.90 per 1,000 successful answers. The Agentic Memory Index v0.1, published in August 2026, measures accuracy, cost, and speed for each tool using the same agent model.

read1 min views1 publishedAug 3, 2026
A Markdown wiki outscored every AI agent memory product we benchmarked
Image: source

We independently measure the tools AI agents use and publish what each one actually adds.

Agentic Memory Indexi #

Methodology Agentic Memory Index v0.1 · Aug 2026

Highlights #

Accuracy, cost, and speed for every tool, measured the same way.

Agentic Memory Indexi

The overall score: how often each tool finds the right answer.

Claude Code built-in memory 67.7

Costi

USD per 1,000 successful answers

Claude Code built-in memory $426.90

Answer speedi

How long an answer takes end to end, same agent model on every tool.

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