--- title: "onnx-mlir vs claude-mem" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/onnx-onnx-mlir-vs-thedotmack-claude-mem" tools: ["onnx-onnx-mlir", "thedotmack-claude-mem"] --- # onnx-mlir vs claude-mem *GraphCanon updated Jul 11, 2026* ## Verdict Pick onnx-mlir when onnx-mlir is primarily C++; claude-mem is JavaScript; pick claude-mem when claude-mem is primarily JavaScript; onnx-mlir is C++. [onnx-mlir](https://github.com/onnx/onnx-mlir) reports 1.0k GitHub stars, 443 forks, and 352 open issues, last pushed Jul 10, 2026. [claude-mem](https://claude-mem.ai) has 87k stars, 7.5k forks, and 252 open issues, last pushed Jul 9, 2026. Figures are from public GitHub metadata via [onnx-mlir's repository](https://github.com/onnx/onnx-mlir) and [claude-mem's repository](https://github.com/thedotmack/claude-mem). | | [onnx-mlir](/tools/onnx-onnx-mlir.md) | [claude-mem](/tools/thedotmack-claude-mem.md) | | --- | --- | --- | | Tagline | Representation and Reference Lowering of ONNX Models in MLIR Compiler Infrastructure | Persistent Context Across Sessions for Every Agent | | Stars | 1,036 | 86,816 | | Forks | 443 | 7,500 | | Open issues | 352 | 252 | | Language | C++ | JavaScript | | Adopt for | - | claude-mem provides persistent context across sessions, leveraging AI to capture and compress agent activity. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Claude-Mem is distributed under the Apache License 2.0, allowing it to be freely used in a variety of development and production environments while maintaining clear licensing terms. | | Categories | Computer Vision, Inference & Serving, Vector Databases | AI Agents, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [onnx-mlir](/tools/onnx-onnx-mlir.md) | [claude-mem](/tools/thedotmack-claude-mem.md) | | --- | --- | --- | | Open issues (now) | 352 | 252 | | Owner type | Organization | User | | Security scan | 3 low (3 low) | No lockfile | | Full report | [trust report](/tools/onnx-onnx-mlir/trust.md) | [trust report](/tools/thedotmack-claude-mem/trust.md) | ## Shared compatibility - **Python**: [onnx-mlir](/tools/onnx-onnx-mlir.md) - Python runtime; [claude-mem](/tools/thedotmack-claude-mem.md) - Python runtime ## Decision facts: claude-mem - **Requirements:** Requires Node.js v20.0.0 or higher.; Must have the latest version of Claude Code with plugin support.; Auto-installs Bun (JavaScript runtime and process manager) if not already present.; Requires uv (Python package for vector search), auto-installation supported. - **Adopt for:** claude-mem provides persistent context across sessions, leveraging AI to capture and compress agent activity. - **License detail:** Claude-Mem is distributed under the Apache License 2.0, allowing it to be freely used in a variety of development and production environments while maintaining clear licensing terms. ## Choose when ### Choose onnx-mlir if… - onnx-mlir is primarily C++; claude-mem is JavaScript. - Tags unique to onnx-mlir: c++. - Also covers Computer Vision, Vector Databases. ### Choose claude-mem if… - claude-mem is primarily JavaScript; onnx-mlir is C++. - Requirements: Requires Node.js v20.0.0 or higher.; Must have the latest version of Claude Code with plugin support.; Auto-installs Bun (JavaScript runtime and process manager) if not already present.; Requires uv (Python package for vector search), auto-installation supported.. - Tags unique to claude-mem: ai-agents, ai-memory, chromadb, claude. - Also covers AI Agents. - When you require seamless and persistent context continuity between different session interactions with Claude Code or other supported agents. ## When NOT to use onnx-mlir - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## When NOT to use claude-mem - When working in environments where Node.js v20.0.0 or higher cannot be installed, as claude-mem requires this version to operate. - If your specific AI agent or tool does not integrate with the supported frameworks listed (e.g., Claude Code, OpenClaw), making context persistence ineffective for your workflow. ## Common questions ### What is the difference between onnx-mlir and claude-mem? onnx-mlir: Representation and Reference Lowering of ONNX Models in MLIR Compiler Infrastructure. claude-mem: Persistent Context Across Sessions for Every Agent. See the comparison table for live GitHub stats and shared categories. ### When should I choose onnx-mlir over claude-mem? Choose onnx-mlir over claude-mem when onnx-mlir is primarily C++; claude-mem is JavaScript; Tags unique to onnx-mlir: c++; Also covers Computer Vision, Vector Databases. ### When should I choose claude-mem over onnx-mlir? Choose claude-mem over onnx-mlir when claude-mem is primarily JavaScript; onnx-mlir is C++; Requirements: Requires Node.js v20.0.0 or higher.; Must have the latest version of Claude Code with plugin support.; Auto-installs Bun (JavaScript runtime and process manager) if not already present.; Requires uv (Python package for vector search), auto-installation supported.; Tags unique to claude-mem: ai-agents, ai-memory, chromadb, claude; Also covers AI Agents; When you require seamless and persistent context continuity between different session interactions with Claude Code or other supported agents. ### When should I avoid onnx-mlir? Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### When should I avoid claude-mem? When working in environments where Node.js v20.0.0 or higher cannot be installed, as claude-mem requires this version to operate. If your specific AI agent or tool does not integrate with the supported frameworks listed (e.g., Claude Code, OpenClaw), making context persistence ineffective for your workflow. ### Is onnx-mlir or claude-mem more popular on GitHub? claude-mem has more GitHub stars (86,816 vs 1,036). Stars measure visibility, not whether either tool fits your constraints. ### Are onnx-mlir and claude-mem open source? Yes - both are open-source projects on GitHub (onnx-mlir: Apache-2.0, claude-mem: Apache-2.0). ### Where can I find alternatives to onnx-mlir or claude-mem? GraphCanon lists graph-backed alternatives at [onnx-mlir alternatives](/tools/onnx-onnx-mlir/alternatives) and [claude-mem alternatives](/tools/thedotmack-claude-mem/alternatives) ([onnx-mlir markdown twin](/tools/onnx-onnx-mlir/alternatives.md), [claude-mem markdown twin](/tools/thedotmack-claude-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/onnx-onnx-mlir-vs-thedotmack-claude-mem.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, onnx-mlir or claude-mem? onnx-mlir: Very active. claude-mem: Very active. 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 onnx-mlir and claude-mem? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [onnx-mlir trust report](/tools/onnx-onnx-mlir/trust); [claude-mem trust report](/tools/thedotmack-claude-mem/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=onnx-onnx-mlir`](/api/graphcanon/graph?tool=onnx-onnx-mlir) - 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/_