--- title: "mempalace vs 3D-Mem" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/mempalace-mempalace-vs-umass-embodied-agi-3d-mem" tools: ["mempalace-mempalace", "umass-embodied-agi-3d-mem"] --- # mempalace vs 3D-Mem *GraphCanon updated Jul 11, 2026* ## Verdict Pick mempalace when tags unique to mempalace: chromadb, llm, memory; pick 3D-Mem when tags unique to 3D-Mem: computer-vision, embodied-ai, python, spatial-intelligence. [mempalace](http://mempalaceofficial.com/) reports 57k GitHub stars, 7.4k forks, and 616 open issues, last pushed Jul 10, 2026. [3D-Mem](https://umass-embodied-agi.github.io/3D-Mem/) has 264 stars, 17 forks, and 3 open issues, last pushed Oct 2, 2025. Figures are from public GitHub metadata via [mempalace's repository](https://github.com/MemPalace/mempalace) and [3D-Mem's repository](https://github.com/UMass-Embodied-AGI/3D-Mem). | | [mempalace](/tools/mempalace-mempalace.md) | [3D-Mem](/tools/umass-embodied-agi-3d-mem.md) | | --- | --- | --- | | Tagline | The best-benchmarked open-source AI memory system. | [CVPR 2025] Source codes for the paper "3D-Mem: 3D Scene Memory for Embodied Exploration and Reasoning" | | Stars | 57,215 | 264 | | Forks | 7,387 | 17 | | Open issues | 616 | 3 | | Language | Python | Python | | Adopt for | MemPalace is an advanced open-source AI memory system that integrates with ChromaDB to optimize machine learning model memories and enhance data retrieval efficiency. | - | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Model Training, Vector Databases | Computer Vision, Model Training, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [mempalace](/tools/mempalace-mempalace.md) | [3D-Mem](/tools/umass-embodied-agi-3d-mem.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 281d | | Open issues (now) | 616 | 3 | | Security scan | No MCP manifest | No lockfile | | Full report | [trust report](/tools/mempalace-mempalace/trust.md) | [trust report](/tools/umass-embodied-agi-3d-mem/trust.md) | ## Decision facts: mempalace - **Adopt for:** MemPalace is an advanced open-source AI memory system that integrates with ChromaDB to optimize machine learning model memories and enhance data retrieval efficiency. ## Choose when ### Choose mempalace if… - Tags unique to mempalace: chromadb, llm, memory. - mempalace ships Docker support for self-hosted deployment. - When you need a highly benchmarked solution for managing AI model memories, MemPalace can provide superior performance due to its optimization features integrated specifically around ML model needs. ### Choose 3D-Mem if… - Tags unique to 3D-Mem: computer-vision, embodied-ai, python, spatial-intelligence. - Also covers Computer Vision. - Leaner open-issue backlog (3). ## When NOT to use mempalace - Avoid if requiring a proprietary system where full transparency or customization of the memory management layer may not be necessary, since MemPalace is open source and might involve deeper technical啃 - "如果你的应用场景对内存管理层的完全透明或定制化需求不高，因为MemPalace是开源的，可能需要更深的技术介入来满足特定需求。" - If your project strictly adheres to non-MIT licenses, then MemPalace might not be suitable due to its MIT license which may conflict with licensing requirements. ## When NOT to use 3D-Mem - Last GitHub push was 282 days ago (slowing maintenance, Oct 2, 2025). Validate activity before betting a new project on 3D-Mem. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between mempalace and 3D-Mem? mempalace: The best-benchmarked open-source AI memory system.. 3D-Mem: [CVPR 2025] Source codes for the paper "3D-Mem: 3D Scene Memory for Embodied Exploration and Reasoning". See the comparison table for live GitHub stats and shared categories. ### When should I choose mempalace over 3D-Mem? Choose mempalace over 3D-Mem when Tags unique to mempalace: chromadb, llm, memory; mempalace ships Docker support for self-hosted deployment; When you need a highly benchmarked solution for managing AI model memories, MemPalace can provide superior performance due to its optimization features integrated specifically around ML model needs. ### When should I choose 3D-Mem over mempalace? Choose 3D-Mem over mempalace when Tags unique to 3D-Mem: computer-vision, embodied-ai, python, spatial-intelligence; Also covers Computer Vision; Leaner open-issue backlog (3). ### When should I avoid mempalace? Avoid if requiring a proprietary system where full transparency or customization of the memory management layer may not be necessary, since MemPalace is open source and might involve deeper technical啃 "如果你的应用场景对内存管理层的完全透明或定制化需求不高，因为MemPalace是开源的，可能需要更深的技术介入来满足特定需求。" If your project strictly adheres to non-MIT licenses, then MemPalace might not be suitable due to its MIT license which may conflict with licensing requirements. ### When should I avoid 3D-Mem? Last GitHub push was 282 days ago (slowing maintenance, Oct 2, 2025). Validate activity before betting a new project on 3D-Mem. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is mempalace or 3D-Mem more popular on GitHub? mempalace has more GitHub stars (57,215 vs 264). Stars measure visibility, not whether either tool fits your constraints. ### Are mempalace and 3D-Mem open source? Yes - both are open-source projects on GitHub (mempalace: MIT, 3D-Mem: MIT). ### Where can I find alternatives to mempalace or 3D-Mem? GraphCanon lists graph-backed alternatives at [mempalace alternatives](/tools/mempalace-mempalace/alternatives) and [3D-Mem alternatives](/tools/umass-embodied-agi-3d-mem/alternatives) ([mempalace markdown twin](/tools/mempalace-mempalace/alternatives.md), [3D-Mem markdown twin](/tools/umass-embodied-agi-3d-mem/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/mempalace-mempalace-vs-umass-embodied-agi-3d-mem.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, mempalace or 3D-Mem? mempalace: Very active. 3D-Mem: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for mempalace and 3D-Mem? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [mempalace trust report](/tools/mempalace-mempalace/trust); [3D-Mem trust report](/tools/umass-embodied-agi-3d-mem/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=mempalace-mempalace`](/api/graphcanon/graph?tool=mempalace-mempalace) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_