--- title: "garak vs ChatGLM-6B" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/nvidia-garak-vs-zai-org-chatglm-6b" tools: ["nvidia-garak", "zai-org-chatglm-6b"] --- # garak vs ChatGLM-6B *GraphCanon updated Jul 11, 2026* ## Verdict Pick garak when tags unique to garak: ai, llm-evaluation, llm-security, security-scanners; pick ChatGLM-6B when also covers Data & Retrieval. [garak](https://discord.gg/uVch4puUCs) reports 8.4k GitHub stars, 1.1k forks, and 367 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 [garak's repository](https://github.com/NVIDIA/garak) and [ChatGLM-6B's repository](https://github.com/zai-org/ChatGLM-6B). | | [garak](/tools/nvidia-garak.md) | [ChatGLM-6B](/tools/zai-org-chatglm-6b.md) | | --- | --- | --- | | Tagline | the LLM vulnerability scanner | ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型 | | Stars | 8,400 | 41,035 | | Forks | 1,079 | 5,132 | | Open issues | 367 | 609 | | Language | Python | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Evaluation & Observability, LLM Frameworks, Vector Databases | Data & Retrieval, LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [garak](/tools/nvidia-garak.md) | [ChatGLM-6B](/tools/zai-org-chatglm-6b.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 1d | 744d | | Open issues (now) | 367 | 609 | | Security scan | 54 low (54 low) | 75 low (75 low) | | Full report | [trust report](/tools/nvidia-garak/trust.md) | [trust report](/tools/zai-org-chatglm-6b/trust.md) | ## Shared compatibility - **Python**: [garak](/tools/nvidia-garak.md) - Python runtime; [ChatGLM-6B](/tools/zai-org-chatglm-6b.md) - Python runtime ## Choose when ### Choose garak if… - Tags unique to garak: ai, llm-evaluation, llm-security, security-scanners. - Also covers Evaluation & Observability. - More recently updated (last pushed Jul 10, 2026). ### Choose ChatGLM-6B if… - Also covers Data & Retrieval. - More GitHub stars (41k vs 8.4k) - visibility, not fit. ## When NOT to use garak - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - 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 ChatGLM-6B - Last GitHub push was 745 days ago (dormant maintenance, Jun 27, 2024). Validate activity before betting a new project on ChatGLM-6B. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - 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 garak and ChatGLM-6B? garak: the LLM vulnerability scanner. 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 garak over ChatGLM-6B? Choose garak over ChatGLM-6B when Tags unique to garak: ai, llm-evaluation, llm-security, security-scanners; Also covers Evaluation & Observability; More recently updated (last pushed Jul 10, 2026). ### When should I choose ChatGLM-6B over garak? Choose ChatGLM-6B over garak when Also covers Data & Retrieval; More GitHub stars (41k vs 8.4k) - visibility, not fit. ### When should I avoid garak? Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. 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 ChatGLM-6B? Last GitHub push was 745 days ago (dormant maintenance, Jun 27, 2024). Validate activity before betting a new project on ChatGLM-6B. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is garak or ChatGLM-6B more popular on GitHub? ChatGLM-6B has more GitHub stars (41,035 vs 8,400). Stars measure visibility, not whether either tool fits your constraints. ### Are garak and ChatGLM-6B open source? Yes - both are open-source projects on GitHub (garak: Apache-2.0, ChatGLM-6B: Apache-2.0). ### Where can I find alternatives to garak or ChatGLM-6B? GraphCanon lists graph-backed alternatives at [garak alternatives](/tools/nvidia-garak/alternatives) and [ChatGLM-6B alternatives](/tools/zai-org-chatglm-6b/alternatives) ([garak markdown twin](/tools/nvidia-garak/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/nvidia-garak-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, garak or ChatGLM-6B? garak: 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 garak and ChatGLM-6B? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [garak trust report](/tools/nvidia-garak/trust); [ChatGLM-6B trust report](/tools/zai-org-chatglm-6b/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=nvidia-garak`](/api/graphcanon/graph?tool=nvidia-garak) - 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/_