--- title: "Model-Fingerprint vs hallucination-index" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/cnut1648-model-fingerprint-vs-rungalileo-hallucination-index" tools: ["cnut1648-model-fingerprint", "rungalileo-hallucination-index"] --- # Model-Fingerprint vs hallucination-index *GraphCanon updated Aug 5, 2026* ## Verdict Pick Model-Fingerprint if model-Fingerprint is a toolset for creating instructional fingerprints of large language models using CUDA 11.3 and PyTorch 2.0; pick hallucination-index if hallucination-Index helps users identify LLMs with the lowest propensity for factual errors across varying context lengths and source types. [Model-Fingerprint](https://github.com/cnut1648/Model-Fingerprint) reports 52 GitHub stars, 8 forks, and 5 open issues, last pushed Jul 11, 2024. [hallucination-index](https://www.rungalileo.io/hallucinationindex) has 116 stars, 8 forks, and 1 open issues, last pushed Jul 28, 2025. Figures are from public GitHub metadata via [Model-Fingerprint's repository](https://github.com/cnut1648/Model-Fingerprint) and [hallucination-index's repository](https://github.com/rungalileo/hallucination-index). | | [Model-Fingerprint](/tools/cnut1648-model-fingerprint.md) | [hallucination-index](/tools/rungalileo-hallucination-index.md) | | --- | --- | --- | | Tagline | Fingerprint large language models | Initiative to evaluate and rank popular LLMs based on hallucination propensity | | Stars | 52 | 116 | | Forks | 8 | 8 | | Open issues | 5 | 1 | | Language | Python | - | | Adopt for | Model-Fingerprint is a toolset for creating instructional fingerprints of large language models using CUDA 11.3 and PyTorch 2.0. | Hallucination-Index helps users identify LLMs with the lowest propensity for factual errors across varying context lengths and source types. | | Persona | - | - | | Runtime | - | - | | License | MIT | - | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Model-Fingerprint](/tools/cnut1648-model-fingerprint.md) | [hallucination-index](/tools/rungalileo-hallucination-index.md) | | --- | --- | --- | | Days since push | 754d | 365d | | Open issues (now) | 5 | 1 | | Owner type | User | Organization | | Full report | [trust report](/tools/cnut1648-model-fingerprint/trust.md) | [trust report](/tools/rungalileo-hallucination-index/trust.md) | ## Decision facts: Model-Fingerprint - **Adopt for:** Model-Fingerprint is a toolset for creating instructional fingerprints of large language models using CUDA 11.3 and PyTorch 2.0. ## Decision facts: hallucination-index - **Adopt for:** Hallucination-Index helps users identify LLMs with the lowest propensity for factual errors across varying context lengths and source types. ## Choose when ### Choose Model-Fingerprint if… - Tags unique to Model-Fingerprint: fingerprinting, pytorch. - Use Model-Fingerprint when you need to fingerprint large language models for evaluation or observability purposes, especially in research contexts involving CUDA 11.3 and PyTorch 2.0 environments. ### Choose hallucination-index if… - Tags unique to hallucination-index: hallucinations, llm-evaluation, openai, rag. - Use when you need to ensure accuracy in short-context tasks, as it tests models like Chain-of-Note prompting techniques specifically for such scenarios. - More GitHub stars (116 vs 52) - visibility, not fit. ## When NOT to use Model-Fingerprint - Do not use Model-Fingerprint if your development environment does not support CUDA 11.3 and PyTorch 2.0, as it may lead to incompatibility issues. - Avoid this toolset if you need a solution that supports multiple versions of CUDA or Pytorch for flexibility across different hardware configurations without modification. ## When NOT to use hallucination-index - Avoid using Hallucination-Index when your application requires real-time evaluation of hallucinations, as it focuses on predefined tests rather than live model performance. - Do not rely solely on this index if your primary concern is the latest updates to LLM models; its data might not reflect recent improvements in models or the introduction of new ones. ## Common questions ### What is the difference between Model-Fingerprint and hallucination-index? Model-Fingerprint: Fingerprint large language models. hallucination-index: Initiative to evaluate and rank popular LLMs based on hallucination propensity. See the comparison table for live GitHub stats and shared categories. ### When should I choose Model-Fingerprint over hallucination-index? Choose Model-Fingerprint over hallucination-index when Tags unique to Model-Fingerprint: fingerprinting, pytorch; Use Model-Fingerprint when you need to fingerprint large language models for evaluation or observability purposes, especially in research contexts involving CUDA 11.3 and PyTorch 2.0 environments. ### When should I choose hallucination-index over Model-Fingerprint? Choose hallucination-index over Model-Fingerprint when Tags unique to hallucination-index: hallucinations, llm-evaluation, openai, rag; Use when you need to ensure accuracy in short-context tasks, as it tests models like Chain-of-Note prompting techniques specifically for such scenarios; More GitHub stars (116 vs 52) - visibility, not fit. ### When should I avoid Model-Fingerprint? Do not use Model-Fingerprint if your development environment does not support CUDA 11.3 and PyTorch 2.0, as it may lead to incompatibility issues. Avoid this toolset if you need a solution that supports multiple versions of CUDA or Pytorch for flexibility across different hardware configurations without modification. ### When should I avoid hallucination-index? Avoid using Hallucination-Index when your application requires real-time evaluation of hallucinations, as it focuses on predefined tests rather than live model performance. Do not rely solely on this index if your primary concern is the latest updates to LLM models; its data might not reflect recent improvements in models or the introduction of new ones. ### Is Model-Fingerprint or hallucination-index more popular on GitHub? hallucination-index has more GitHub stars (116 vs 52). Stars measure visibility, not whether either tool fits your constraints. ### Are Model-Fingerprint and hallucination-index open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to Model-Fingerprint or hallucination-index? GraphCanon lists graph-backed alternatives at [Model-Fingerprint alternatives](/tools/cnut1648-model-fingerprint/alternatives) and [hallucination-index alternatives](/tools/rungalileo-hallucination-index/alternatives) ([Model-Fingerprint markdown twin](/tools/cnut1648-model-fingerprint/alternatives.md), [hallucination-index markdown twin](/tools/rungalileo-hallucination-index/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/cnut1648-model-fingerprint-vs-rungalileo-hallucination-index.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Model-Fingerprint or hallucination-index? Model-Fingerprint: Dormant. hallucination-index: 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 Model-Fingerprint and hallucination-index? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Model-Fingerprint trust report](/tools/cnut1648-model-fingerprint/trust); [hallucination-index trust report](/tools/rungalileo-hallucination-index/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=cnut1648-model-fingerprint`](/api/graphcanon/graph?tool=cnut1648-model-fingerprint) - 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/_