--- title: "chain-of-thought-hub vs hallucination-index" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/franxyao-chain-of-thought-hub-vs-rungalileo-hallucination-index" tools: ["franxyao-chain-of-thought-hub", "rungalileo-hallucination-index"] --- # chain-of-thought-hub vs hallucination-index *GraphCanon updated Aug 6, 2026* ## Verdict Pick chain-of-thought-hub if chain-of-Thought Hub measures the performance of large language models (LLMs) on complex tasks by using carefully selected datasets across various domains such as math, science, coding, and knowledge. It evaluates if LLM; pick hallucination-index if hallucination-Index helps users identify LLMs with the lowest propensity for factual errors across varying context lengths and source types. [chain-of-thought-hub](https://github.com/FranxYao/chain-of-thought-hub) reports 2.8k GitHub stars, 144 forks, and 27 open issues, last pushed Aug 4, 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 [chain-of-thought-hub's repository](https://github.com/FranxYao/chain-of-thought-hub) and [hallucination-index's repository](https://github.com/rungalileo/hallucination-index). | | [chain-of-thought-hub](/tools/franxyao-chain-of-thought-hub.md) | [hallucination-index](/tools/rungalileo-hallucination-index.md) | | --- | --- | --- | | Tagline | Benchmarking large language models' complex reasoning ability with chain-of-thought prompting | Initiative to evaluate and rank popular LLMs based on hallucination propensity | | Stars | 2,774 | 116 | | Forks | 144 | 8 | | Open issues | 27 | 1 | | Language | Jupyter Notebook | - | | Adopt for | Chain-of-Thought Hub measures the performance of large language models (LLMs) on complex tasks by using carefully selected datasets across various domains such as math, science, coding, and knowledge. It evaluates if LLM | Hallucination-Index helps users identify LLMs with the lowest propensity for factual errors across varying context lengths and source types. | | Persona | - | - | | Runtime | - | - | | License | The MIT license permits the use of Chain-of-Thought Hub in both open source and commercial projects with acknowledgment. | - | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [chain-of-thought-hub](/tools/franxyao-chain-of-thought-hub.md) | [hallucination-index](/tools/rungalileo-hallucination-index.md) | | --- | --- | --- | | Days since push | 732d | 365d | | Open issues (now) | 27 | 1 | | Owner type | User | Organization | | Full report | [trust report](/tools/franxyao-chain-of-thought-hub/trust.md) | [trust report](/tools/rungalileo-hallucination-index/trust.md) | ## Decision facts: chain-of-thought-hub - **Requirements:** Min 8 GB RAM; Chain-of-Thought Hub is designed to be integrated into environments for evaluating LLMs using Jupyter Notebooks - **Adopt for:** Chain-of-Thought Hub measures the performance of large language models (LLMs) on complex tasks by using carefully selected datasets across various domains such as math, science, coding, and knowledge. It evaluates if LLM - **License detail:** The MIT license permits the use of Chain-of-Thought Hub in both open source and commercial projects with acknowledgment. ## 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 chain-of-thought-hub if… - Requirements: Min 8 GB RAM; Chain-of-Thought Hub is designed to be integrated into environments for evaluating LLMs using Jupyter Notebooks. - Tags unique to chain-of-thought-hub: chain-of-thought prompting, complex reasoning, llm-benchmarking. - Use Chain-of-Thought Hub when you need to benchmark smaller LLMs against larger ones for complex reasoning abilities. ### Choose hallucination-index if… - Tags unique to hallucination-index: hallucinations, large language models, llm-evaluation, openai. - 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 recently updated (last pushed Jul 28, 2025). ## When NOT to use chain-of-thought-hub - Do not use Chain-of-Thought Hub if your focus is on general conversational capabilities rather than specific, challenging problem-solving tasks. - Avoid this tool if you are primarily interested in simpler language processing tasks that do not involve chain-of-thought prompting or complex datasets. ## 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 chain-of-thought-hub and hallucination-index? chain-of-thought-hub: Benchmarking large language models' complex reasoning ability with chain-of-thought prompting. 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 chain-of-thought-hub over hallucination-index? Choose chain-of-thought-hub over hallucination-index when Requirements: Min 8 GB RAM; Chain-of-Thought Hub is designed to be integrated into environments for evaluating LLMs using Jupyter Notebooks; Tags unique to chain-of-thought-hub: chain-of-thought prompting, complex reasoning, llm-benchmarking; Use Chain-of-Thought Hub when you need to benchmark smaller LLMs against larger ones for complex reasoning abilities. ### When should I choose hallucination-index over chain-of-thought-hub? Choose hallucination-index over chain-of-thought-hub when Tags unique to hallucination-index: hallucinations, large language models, llm-evaluation, openai; 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 recently updated (last pushed Jul 28, 2025). ### When should I avoid chain-of-thought-hub? Do not use Chain-of-Thought Hub if your focus is on general conversational capabilities rather than specific, challenging problem-solving tasks. Avoid this tool if you are primarily interested in simpler language processing tasks that do not involve chain-of-thought prompting or complex datasets. ### 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 chain-of-thought-hub or hallucination-index more popular on GitHub? chain-of-thought-hub has more GitHub stars (2,774 vs 116). Stars measure visibility, not whether either tool fits your constraints. ### Are chain-of-thought-hub and hallucination-index open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to chain-of-thought-hub or hallucination-index? GraphCanon lists graph-backed alternatives at [chain-of-thought-hub alternatives](/tools/franxyao-chain-of-thought-hub/alternatives) and [hallucination-index alternatives](/tools/rungalileo-hallucination-index/alternatives) ([chain-of-thought-hub markdown twin](/tools/franxyao-chain-of-thought-hub/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/franxyao-chain-of-thought-hub-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, chain-of-thought-hub or hallucination-index? chain-of-thought-hub: 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 chain-of-thought-hub and hallucination-index? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [chain-of-thought-hub trust report](/tools/franxyao-chain-of-thought-hub/trust); [hallucination-index trust report](/tools/rungalileo-hallucination-index/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=franxyao-chain-of-thought-hub`](/api/graphcanon/graph?tool=franxyao-chain-of-thought-hub) - 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/_