hallucination-index
Initiative to evaluate and rank popular LLMs based on hallucination propensity
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
Hallucination-Index helps users identify LLMs with the lowest propensity for factual errors across varying context lengths and source types.
Good fit when
- 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.
- Choose this tool if you wish to compare both open-source and closed-source LLMs; its methodology assesses the performance gap between different source types under similar test parameters.
Avoid when
- 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.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (418d since push)
- As of Sep 20, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 20, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/rungalileo/hallucination-indexSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
The repository evaluates the tendency of large language models (LLMs) to generate factual errors, known as 'hallucinations,' by testing model attributes such as context length and source openness. It includes a comprehensive assessment of 22 open-source and closed-source models using various prompting techniques across short, medium, and long contexts.
Capability facts
No sourced capability facts yet. Facts appear after ingest scans repo manifests (Dockerfile, package.json, MCP configs).
Categories
Tags
README
🌟 LLM Hallucination Index RAG Special 🌟 <p align="center" <img src="/images/2025 LLM Hallucination Index.png" / </p <p align="center" <a href="https://galileo.ai/hallucination index" https://galileo.ai/hallucination index</a </p About the Index <p align="center" <img src="image...
For agents
This page has a .md twin and JSON over the API.