--- title: "last_layer vs hallucination-index" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/arekusandr-last-layer-vs-rungalileo-hallucination-index" tools: ["arekusandr-last-layer", "rungalileo-hallucination-index"] --- # last_layer vs hallucination-index *GraphCanon updated Sep 20, 2026* ## Verdict Pick last_layer if an ultra-fast Python tool for detecting prompt injections and jailbreak attempts in large language models suitable for projects requiring rapid security evaluations, with low-latency performance; pick hallucination-index if hallucination-Index helps users identify LLMs with the lowest propensity for factual errors across varying context lengths and source types. [last_layer](https://vibe-eval.com) reports 133 GitHub stars, 6 forks, and 13 open issues, last pushed Jul 26, 2024. [hallucination-index](https://www.rungalileo.io/hallucinationindex) has 115 stars, 8 forks, and 1 open issues, last pushed Jul 28, 2025. Figures are from public GitHub metadata via [last_layer's repository](https://github.com/arekusandr/last_layer) and [hallucination-index's repository](https://github.com/rungalileo/hallucination-index). | | [last_layer](/tools/arekusandr-last-layer.md) | [hallucination-index](/tools/rungalileo-hallucination-index.md) | | --- | --- | --- | | Tagline | Ultra-fast low latency LLM prompt injection jailbreak detection | Initiative to evaluate and rank popular LLMs based on hallucination propensity | | Stars | 133 | 115 | | Forks | 6 | 8 | | Open issues | 13 | 1 | | Language | Python | - | | Adopt for | An ultra-fast Python tool for detecting prompt injections and jailbreak attempts in large language models suitable for projects requiring rapid security evaluations, with low-latency performance. | 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._ | | [last_layer](/tools/arekusandr-last-layer.md) | [hallucination-index](/tools/rungalileo-hallucination-index.md) | | --- | --- | --- | | Days since push | 780d | 418d | | Open issues (now) | 13 | 1 | | Stars delta | +2 (30d) | -1 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/arekusandr-last-layer/trust.md) | [trust report](/tools/rungalileo-hallucination-index/trust.md) | ## Decision facts: last_layer - **Adopt for:** An ultra-fast Python tool for detecting prompt injections and jailbreak attempts in large language models suitable for projects requiring rapid security evaluations, with low-latency performance. ## 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 last_layer if… - Tags unique to last_layer: chatgpt-prompts, jailbreak, llm-guard, llm-guardrails. - When you need fast detection of potential security vulnerabilities due to unauthorized prompt manipulations in real-time scenarios involving LLMs - More GitHub stars (133 vs 115) - visibility, not fit. ### 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 recently updated (last pushed Jul 28, 2025). ## When NOT to use last_layer - If your application does not require ultra-low latency detection and can afford slower, potentially more comprehensive security evaluations - For environments that prefer a broader range of security features beyond prompt injection detection, as last_layer focuses specifically on this aspect with speed in mind ## 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 last_layer and hallucination-index? last_layer: Ultra-fast low latency LLM prompt injection jailbreak detection. 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 last_layer over hallucination-index? Choose last_layer over hallucination-index when Tags unique to last_layer: chatgpt-prompts, jailbreak, llm-guard, llm-guardrails; When you need fast detection of potential security vulnerabilities due to unauthorized prompt manipulations in real-time scenarios involving LLMs; More GitHub stars (133 vs 115) - visibility, not fit. ### When should I choose hallucination-index over last_layer? Choose hallucination-index over last_layer 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 recently updated (last pushed Jul 28, 2025). ### When should I avoid last_layer? If your application does not require ultra-low latency detection and can afford slower, potentially more comprehensive security evaluations For environments that prefer a broader range of security features beyond prompt injection detection, as last_layer focuses specifically on this aspect with speed in mind ### 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 last_layer or hallucination-index more popular on GitHub? last_layer has more GitHub stars (133 vs 115). Stars measure visibility, not whether either tool fits your constraints. ### Are last_layer and hallucination-index open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to last_layer or hallucination-index? GraphCanon lists graph-backed alternatives at [last_layer alternatives](/tools/arekusandr-last-layer/alternatives) and [hallucination-index alternatives](/tools/rungalileo-hallucination-index/alternatives) ([last_layer markdown twin](/tools/arekusandr-last-layer/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/arekusandr-last-layer-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, last_layer or hallucination-index? last_layer: 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 last_layer and hallucination-index? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [last_layer trust report](/tools/arekusandr-last-layer/trust); [hallucination-index trust report](/tools/rungalileo-hallucination-index/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=arekusandr-last-layer`](/api/graphcanon/graph?tool=arekusandr-last-layer) - 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/_