--- title: "LLM-VM vs LLMmap" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/anarchy-ai-llm-vm-vs-pasquini-dario-llmmap" tools: ["anarchy-ai-llm-vm", "pasquini-dario-llmmap"] --- # LLM-VM vs LLMmap *GraphCanon updated Oct 5, 2026* ## Verdict Pick LLM-VM if lLM-VM is a Python-based repository aimed at LLM development, highlighting tools for distillation, training, and inference; pick LLMmap if lLMmap is a Python-based tool for quick inference using pretrained models without needing additional training. It includes PyTorch weights, configuration files, and behavioral templates tailored to 52 different LLMs. [LLM-VM](https://anarchy.ai/) reports 492 GitHub stars, 139 forks, and 130 open issues, last pushed May 14, 2024. [LLMmap](https://github.com/pasquini-dario/LLMmap) has 469 stars, 51 forks, and 6 open issues, last pushed Jul 24, 2025. Figures are from public GitHub metadata via [LLM-VM's repository](https://github.com/anarchy-ai/LLM-VM) and [LLMmap's repository](https://github.com/pasquini-dario/LLMmap). | | [LLM-VM](/tools/anarchy-ai-llm-vm.md) | [LLMmap](/tools/pasquini-dario-llmmap.md) | | --- | --- | --- | | Tagline | irresponsible innovation | Provides a ready-to-use pretrained model for open-set inference with PyTorch weights, configuration file, and behavioral templates. | | Stars | 492 | 469 | | Forks | 139 | 51 | | Open issues | 130 | 6 | | Language | Python | Python | | Adopt for | LLM-VM is a Python-based repository aimed at LLM development, highlighting tools for distillation, training, and inference. | LLMmap is a Python-based tool for quick inference using pretrained models without needing additional training. It includes PyTorch weights, configuration files, and behavioral templates tailored to 52 different LLMs. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Inference & Serving, LLM Frameworks, Model Training | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LLM-VM](/tools/anarchy-ai-llm-vm.md) | [LLMmap](/tools/pasquini-dario-llmmap.md) | | --- | --- | --- | | Days since push | 858d | 437d | | Open issues (now) | 130 | 6 | | Stars delta | +1 (30d) | +25 (30d) | | Open issues delta | -1 (30d) | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/anarchy-ai-llm-vm/trust.md) | [trust report](/tools/pasquini-dario-llmmap/trust.md) | ## Shared compatibility - **Python**: [LLM-VM](/tools/anarchy-ai-llm-vm.md) - Python runtime; [LLMmap](/tools/pasquini-dario-llmmap.md) - Python runtime ## Decision facts: LLM-VM - **Adopt for:** LLM-VM is a Python-based repository aimed at LLM development, highlighting tools for distillation, training, and inference. ## Decision facts: LLMmap - **Adopt for:** LLMmap is a Python-based tool for quick inference using pretrained models without needing additional training. It includes PyTorch weights, configuration files, and behavioral templates tailored to 52 different LLMs. ## Choose when ### Choose LLM-VM if… - Tags unique to LLM-VM: artificial-intelligence, deep-learning, distillation, llm-agent. - Also covers LLM Frameworks. - LLM-VM ships Docker support for self-hosted deployment. - When you need streamlined processes for model distillation in your project. ### Choose LLMmap if… - Tags unique to LLMmap: llms, open-set inference, pretrained-models, python. - When you need immediate model deployment and don't want or can’t afford the time to train a custom model. - More recently updated (last pushed Jul 24, 2025). ## When NOT to use LLM-VM - Avoid if strict adherence to responsible AI principles is a requirement. - Not recommended for large-scale commercial deployments that necessitate stable and thoroughly validated tools. ## When NOT to use LLMmap - If your application requires fine-tuning on specific datasets as LLMmap offers only generic pretrained models without out-of-the-box support for further training. - In scenarios needing advanced customization beyond the provided behavioral templates, since LLMmap’s framework might not accommodate extensive model modifications. ## Common questions ### What is the difference between LLM-VM and LLMmap? LLM-VM: irresponsible innovation. LLMmap: Provides a ready-to-use pretrained model for open-set inference with PyTorch weights, configuration file, and behavioral templates.. See the comparison table for live GitHub stats and shared categories. ### When should I choose LLM-VM over LLMmap? Choose LLM-VM over LLMmap when Tags unique to LLM-VM: artificial-intelligence, deep-learning, distillation, llm-agent; Also covers LLM Frameworks; LLM-VM ships Docker support for self-hosted deployment; When you need streamlined processes for model distillation in your project. ### When should I choose LLMmap over LLM-VM? Choose LLMmap over LLM-VM when Tags unique to LLMmap: llms, open-set inference, pretrained-models, python; When you need immediate model deployment and don't want or can’t afford the time to train a custom model; More recently updated (last pushed Jul 24, 2025). ### When should I avoid LLM-VM? Avoid if strict adherence to responsible AI principles is a requirement. Not recommended for large-scale commercial deployments that necessitate stable and thoroughly validated tools. ### When should I avoid LLMmap? If your application requires fine-tuning on specific datasets as LLMmap offers only generic pretrained models without out-of-the-box support for further training. In scenarios needing advanced customization beyond the provided behavioral templates, since LLMmap’s framework might not accommodate extensive model modifications. ### Is LLM-VM or LLMmap more popular on GitHub? LLM-VM has more GitHub stars (492 vs 469). Stars measure visibility, not whether either tool fits your constraints. ### Are LLM-VM and LLMmap open source? Yes - both are open-source projects on GitHub (LLM-VM: MIT, LLMmap: MIT). ### Where can I find alternatives to LLM-VM or LLMmap? GraphCanon lists graph-backed alternatives at [LLM-VM alternatives](/tools/anarchy-ai-llm-vm/alternatives) and [LLMmap alternatives](/tools/pasquini-dario-llmmap/alternatives) ([LLM-VM markdown twin](/tools/anarchy-ai-llm-vm/alternatives.md), [LLMmap markdown twin](/tools/pasquini-dario-llmmap/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/anarchy-ai-llm-vm-vs-pasquini-dario-llmmap.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LLM-VM or LLMmap? LLM-VM: Dormant. LLMmap: 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 LLM-VM and LLMmap? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LLM-VM trust report](/tools/anarchy-ai-llm-vm/trust); [LLMmap trust report](/tools/pasquini-dario-llmmap/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=anarchy-ai-llm-vm`](/api/graphcanon/graph?tool=anarchy-ai-llm-vm) - 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/_