MemPalace vs Mem0 vs Zep: AI Memory Tools Compared (2026)

AI Memory Tools: Which One Should You Use?

If you're building with AI or just want your AI to remember past conversations, you've probably come across MemPalace, Mem0, and Zep. They all solve the same core problem — giving AI long-term memory — but with fundamentally different approaches.

Here's an honest comparison based on published benchmarks and architecture analysis.

Quick Comparison

The Architecture Difference

MemPalace: Keep Everything

MemPalace's core philosophy is simple: don't throw anything away. Instead of using an LLM to decide what's "important" (and losing context in the process), MemPalace stores every conversation fragment verbatim with semantic embeddings.

When you search, it uses vector similarity (cosine distance with all-MiniLM-L6-v2) to find relevant fragments. This approach achieves 96.6% recall because no information is lost during storage.

Pros:

• Highest recall accuracy
• No information loss
• No ongoing AI costs for extraction
• Fully open source (MIT)

Cons:

• Larger storage footprint
• No automatic summarization
• Classification is keyword-based (not AI-driven)

Mem0: AI Extracts What Matters

Mem0 uses LLMs to analyze conversations and extract "memories" — key facts, preferences, and decisions. This creates a compact, structured memory that's easy to query.

Pros:

• Compact storage
• Structured memories
• Good API design

Cons:

• AI decides what to keep (49-85% recall)
• Ongoing LLM costs for extraction
• Can miss nuanced context
• $19-249/month

Zep: Hybrid Approach

Zep combines extraction with RAG (Retrieval-Augmented Generation), keeping some raw data while also extracting structured facts.

Pros:

• Balance of structure and raw data
• Good for enterprise use cases
• Automatic fact extraction

Cons:

• 63.8% recall (better than pure extraction, worse than verbatim)
• Complex setup
• $25+/month minimum

Benchmark Details

LongMemEval (ICLR 2025)

LongMemEval is an academic benchmark with 500 questions across 6 question types, testing how well memory systems can retrieve information from long conversation histories.

• MemPalace: 96.6% R@5 (raw verbatim mode)
• Mem0: 49-85% depending on configuration
• Zep: 63.8%

The key insight: simple verbatim storage with good embeddings consistently beats sophisticated AI extraction.

ConvoMem (Salesforce)

ConvoMem tests memory systems on 75,336 QA pairs from real conversations.

• MemPalace: 92.9%
• Mem0: 30-45%
• Long-context approaches: 70-82%

Which Should You Choose?

Choose MemPalace if:

• You want the highest recall accuracy
• You value keeping raw conversations (no AI editing)
• You want a free, open-source solution
• You use MCP-compatible tools (Claude, Cursor)
• You want a simple setup (especially the web version)

Choose Mem0 if:

• You're building a product that needs memory via API
• Storage efficiency matters more than recall
• You want structured, queryable memories
• You have budget for monthly SaaS fees

Choose Zep if:

• You're building enterprise applications
• You need both extraction and raw retrieval
• You want managed infrastructure
• You need team/multi-user support

Try MemPalace

The fastest way to try MemPalace is the web version at mempalace.me. Upload your ChatGPT export, get semantic search + MCP endpoint in 60 seconds. No Python required.

For the full local experience:

pip install mempalace
mempalace mine ~/chats/ --mode convos
mempalace search "your query here"

GitHub Repository →