--- title: "onnx-mlir vs ChatGLM-6B" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/onnx-onnx-mlir-vs-zai-org-chatglm-6b" tools: ["onnx-onnx-mlir", "zai-org-chatglm-6b"] --- # onnx-mlir vs ChatGLM-6B *GraphCanon updated Jul 11, 2026* ## Verdict Pick onnx-mlir when onnx-mlir is primarily C++; ChatGLM-6B is Python; pick ChatGLM-6B when chatGLM-6B is primarily Python; 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. [ChatGLM-6B](https://github.com/zai-org/ChatGLM-6B) has 41k stars, 5.1k forks, and 609 open issues, last pushed Jun 27, 2024. Figures are from public GitHub metadata via [onnx-mlir's repository](https://github.com/onnx/onnx-mlir) and [ChatGLM-6B's repository](https://github.com/zai-org/ChatGLM-6B). | | [onnx-mlir](/tools/onnx-onnx-mlir.md) | [ChatGLM-6B](/tools/zai-org-chatglm-6b.md) | | --- | --- | --- | | Tagline | Representation and Reference Lowering of ONNX Models in MLIR Compiler Infrastructure | ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型 | | Stars | 1,036 | 41,035 | | Forks | 443 | 5,132 | | Open issues | 352 | 609 | | Language | C++ | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Vector Databases, Inference & Serving, Computer Vision | LLM Frameworks, Data & Retrieval, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [onnx-mlir](/tools/onnx-onnx-mlir.md) | [ChatGLM-6B](/tools/zai-org-chatglm-6b.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 1d | 744d | | Open issues (now) | 352 | 609 | | Security scan | 3 low (3 low) | 75 low (75 low) | | Full report | [trust report](/tools/onnx-onnx-mlir/trust.md) | [trust report](/tools/zai-org-chatglm-6b/trust.md) | ## Shared compatibility - **Python**: [onnx-mlir](/tools/onnx-onnx-mlir.md) - Python runtime; [ChatGLM-6B](/tools/zai-org-chatglm-6b.md) - Python runtime ## Choose when ### Choose onnx-mlir if… - onnx-mlir is primarily C++; ChatGLM-6B is Python. - Tags unique to onnx-mlir: c++. - Also covers Inference & Serving, Computer Vision. ### Choose ChatGLM-6B if… - ChatGLM-6B is primarily Python; onnx-mlir is C++. - Tags unique to ChatGLM-6B: python. - Also covers LLM Frameworks, Data & Retrieval. ## When NOT to use onnx-mlir - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## When NOT to use ChatGLM-6B - Last GitHub push was 745 days ago (dormant maintenance, Jun 27, 2024). Validate activity before betting a new project on ChatGLM-6B. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - 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 onnx-mlir and ChatGLM-6B? onnx-mlir: Representation and Reference Lowering of ONNX Models in MLIR Compiler Infrastructure. ChatGLM-6B: ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型. See the comparison table for live GitHub stats and shared categories. ### When should I choose onnx-mlir over ChatGLM-6B? Choose onnx-mlir over ChatGLM-6B when onnx-mlir is primarily C++; ChatGLM-6B is Python; Tags unique to onnx-mlir: c++; Also covers Inference & Serving, Computer Vision. ### When should I choose ChatGLM-6B over onnx-mlir? Choose ChatGLM-6B over onnx-mlir when ChatGLM-6B is primarily Python; onnx-mlir is C++; Tags unique to ChatGLM-6B: python; Also covers LLM Frameworks, Data & Retrieval. ### When should I avoid onnx-mlir? Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### When should I avoid ChatGLM-6B? Last GitHub push was 745 days ago (dormant maintenance, Jun 27, 2024). Validate activity before betting a new project on ChatGLM-6B. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is onnx-mlir or ChatGLM-6B more popular on GitHub? ChatGLM-6B has more GitHub stars (41,035 vs 1,036). Stars measure visibility, not whether either tool fits your constraints. ### Are onnx-mlir and ChatGLM-6B open source? Yes - both are open-source projects on GitHub (onnx-mlir: Apache-2.0, ChatGLM-6B: Apache-2.0). ### Where can I find alternatives to onnx-mlir or ChatGLM-6B? GraphCanon lists graph-backed alternatives at [onnx-mlir alternatives](/tools/onnx-onnx-mlir/alternatives) and [ChatGLM-6B alternatives](/tools/zai-org-chatglm-6b/alternatives) ([onnx-mlir markdown twin](/tools/onnx-onnx-mlir/alternatives.md), [ChatGLM-6B markdown twin](/tools/zai-org-chatglm-6b/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-zai-org-chatglm-6b.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, onnx-mlir or ChatGLM-6B? onnx-mlir: Very active. ChatGLM-6B: Dormant. 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 ChatGLM-6B? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [onnx-mlir trust report](/tools/onnx-onnx-mlir/trust); [ChatGLM-6B trust report](/tools/zai-org-chatglm-6b/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/_