---
title: "deepeval vs hallucination-index"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/confident-ai-deepeval-vs-rungalileo-hallucination-index"
tools: ["confident-ai-deepeval", "rungalileo-hallucination-index"]
---

# deepeval vs hallucination-index

*GraphCanon updated Jul 29, 2026*

## Verdict

Pick deepeval if deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies; pick hallucination-index if hallucination-Index helps users identify LLMs with the lowest propensity for factual errors across varying context lengths and source types.

[deepeval](https://deepeval.com) reports 17k GitHub stars, 1.7k forks, and 404 open issues, last pushed Jul 27, 2026. [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 [deepeval's repository](https://github.com/confident-ai/deepeval) and [hallucination-index's repository](https://github.com/rungalileo/hallucination-index).

| | [deepeval](/tools/confident-ai-deepeval.md) | [hallucination-index](/tools/rungalileo-hallucination-index.md) |
| --- | --- | --- |
| Tagline | LLM Evaluation Framework. | Initiative to evaluate and rank popular LLMs based on hallucination propensity |
| Stars | 17,226 | 116 |
| Forks | 1,736 | 8 |
| Open issues | 404 | 1 |
| Language | Python | - |
| Adopt for | Deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies. | Hallucination-Index helps users identify LLMs with the lowest propensity for factual errors across varying context lengths and source types. |
| Persona | - | - |
| Runtime | - | - |
| License | Apache-2.0 License | - |
| Categories | Evaluation & Observability | Evaluation & Observability |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [deepeval](/tools/confident-ai-deepeval.md) | [hallucination-index](/tools/rungalileo-hallucination-index.md) |
| --- | --- | --- |
| Maintenance | Very active (96%) | Dormant (18%) |
| Days since push | 1d | 365d |
| Open issues (now) | 404 | 1 |
| Full report | [trust report](/tools/confident-ai-deepeval/trust.md) | [trust report](/tools/rungalileo-hallucination-index/trust.md) |

## Decision facts: deepeval

- **Requirements:** Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities.
- **Adopt for:** Deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies.
- **License detail:** Apache-2.0 License

## 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 deepeval if…

- Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities..
- Tags unique to deepeval: evaluation, metrics.
- When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics.

### Choose hallucination-index if…

- Tags unique to hallucination-index: hallucinations, large language models, 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.
- Leaner open-issue backlog (1).

## When NOT to use deepeval

- For small-scale applications that do not require the depth of metrics and evaluations offered by Deepeval, as it might be overkill.
- In situations where there is a need for real-time performance monitoring, since Deepeval focuses more on post-development evaluation rather than continuous runtime analysis.

## 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 deepeval and hallucination-index?

deepeval: LLM Evaluation Framework.. 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 deepeval over hallucination-index?

Choose deepeval over hallucination-index when Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities.; Tags unique to deepeval: evaluation, metrics; When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics.

### When should I choose hallucination-index over deepeval?

Choose hallucination-index over deepeval when Tags unique to hallucination-index: hallucinations, large language models, 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; Leaner open-issue backlog (1).

### When should I avoid deepeval?

For small-scale applications that do not require the depth of metrics and evaluations offered by Deepeval, as it might be overkill. In situations where there is a need for real-time performance monitoring, since Deepeval focuses more on post-development evaluation rather than continuous runtime analysis.

### 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 deepeval or hallucination-index more popular on GitHub?

deepeval has more GitHub stars (17,226 vs 116). Stars measure visibility, not whether either tool fits your constraints.

### Are deepeval and hallucination-index open source?

Yes - both are open-source projects on GitHub.

### Where can I find alternatives to deepeval or hallucination-index?

GraphCanon lists graph-backed alternatives at [deepeval alternatives](/tools/confident-ai-deepeval/alternatives) and [hallucination-index alternatives](/tools/rungalileo-hallucination-index/alternatives) ([deepeval markdown twin](/tools/confident-ai-deepeval/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/confident-ai-deepeval-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, deepeval or hallucination-index?

deepeval: Very active. 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 deepeval and hallucination-index?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [deepeval trust report](/tools/confident-ai-deepeval/trust); [hallucination-index trust report](/tools/rungalileo-hallucination-index/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=confident-ai-deepeval`](/api/graphcanon/graph?tool=confident-ai-deepeval)
- 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/_