--- title: "deepeval vs raga-llm-hub" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/confident-ai-deepeval-vs-raga-ai-hub-raga-llm-hub" tools: ["confident-ai-deepeval", "raga-ai-hub-raga-llm-hub"] --- # deepeval vs raga-llm-hub *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 raga-llm-hub if raga LLM-Hub is a Python-based framework for evaluating large language models, enforcing guardrails, and ensuring security during the operation of these models. [deepeval](https://deepeval.com) reports 17k GitHub stars, 1.7k forks, and 404 open issues, last pushed Jul 27, 2026. [raga-llm-hub](https://www.raga.ai/llms) has 114 stars, 14 forks, and 2 open issues, last pushed Sep 9, 2024. Figures are from public GitHub metadata via [deepeval's repository](https://github.com/confident-ai/deepeval) and [raga-llm-hub's repository](https://github.com/raga-ai-hub/raga-llm-hub). | | [deepeval](/tools/confident-ai-deepeval.md) | [raga-llm-hub](/tools/raga-ai-hub-raga-llm-hub.md) | | --- | --- | --- | | Tagline | LLM Evaluation Framework. | Framework for LLM evaluation, guardrails and security | | Stars | 17,226 | 114 | | Forks | 1,736 | 14 | | Open issues | 404 | 2 | | Language | Python | Python | | Adopt for | Deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies. | Raga LLM-Hub is a Python-based framework for evaluating large language models, enforcing guardrails, and ensuring security during the operation of these models. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 License | The license for Raga LLM-Hub differs from common Open Source licenses like MIT or Apache, implying specific conditions that might affect its usability in open projects. | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [deepeval](/tools/confident-ai-deepeval.md) | [raga-llm-hub](/tools/raga-ai-hub-raga-llm-hub.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 1d | 687d | | Open issues (now) | 404 | 2 | | Full report | [trust report](/tools/confident-ai-deepeval/trust.md) | [trust report](/tools/raga-ai-hub-raga-llm-hub/trust.md) | ## Shared compatibility - **Python**: [deepeval](/tools/confident-ai-deepeval.md) - Python runtime; [raga-llm-hub](/tools/raga-ai-hub-raga-llm-hub.md) - Python runtime ## 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: raga-llm-hub - **Pricing:** unknown - Pricing information is not specified; it operates under a unique licensing model which may or may not have restrictive terms for commercial use. - **Requirements:** Requires Python installation and environment to set up.; Installation is straightforward through pip but the broader dependencies should be checked as per project requirements. - **Adopt for:** Raga LLM-Hub is a Python-based framework for evaluating large language models, enforcing guardrails, and ensuring security during the operation of these models. - **License detail:** The license for Raga LLM-Hub differs from common Open Source licenses like MIT or Apache, implying specific conditions that might affect its usability in open projects. ## Choose when ### Choose deepeval if… - License: deepeval is Apache-2.0, raga-llm-hub is Other. - 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 raga-llm-hub if… - License: raga-llm-hub is Other, deepeval is Apache-2.0. - Pricing: Pricing information is not specified; it operates under a unique licensing model which may or may not have restrictive terms for commercial use.. - Requirements: Requires Python installation and environment to set up.; Installation is straightforward through pip but the broader dependencies should be checked as per project requirements.. - Tags unique to raga-llm-hub: guardrails, llm security, llmops. - When you need to conduct detailed evaluations on large language models and require specific methods to enforce guardrails and maintain security within your application or environment. ## 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 raga-llm-hub - If you are working in an environment where the use of Python is not feasible or desired, as Raga LLM-Hub's functionality is deeply integrated within Python. - Avoid using if your primary need does not include guardrails enforcement and security features for LLMs, since Raga LLM Hub emphasizes these aspects. ## Common questions ### What is the difference between deepeval and raga-llm-hub? deepeval: LLM Evaluation Framework.. raga-llm-hub: Framework for LLM evaluation, guardrails and security. See the comparison table for live GitHub stats and shared categories. ### When should I choose deepeval over raga-llm-hub? Choose deepeval over raga-llm-hub when License: deepeval is Apache-2.0, raga-llm-hub is Other; 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 raga-llm-hub over deepeval? Choose raga-llm-hub over deepeval when License: raga-llm-hub is Other, deepeval is Apache-2.0; Pricing: Pricing information is not specified; it operates under a unique licensing model which may or may not have restrictive terms for commercial use.; Requirements: Requires Python installation and environment to set up.; Installation is straightforward through pip but the broader dependencies should be checked as per project requirements.; Tags unique to raga-llm-hub: guardrails, llm security, llmops; When you need to conduct detailed evaluations on large language models and require specific methods to enforce guardrails and maintain security within your application or environment. ### 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 raga-llm-hub? If you are working in an environment where the use of Python is not feasible or desired, as Raga LLM-Hub's functionality is deeply integrated within Python. Avoid using if your primary need does not include guardrails enforcement and security features for LLMs, since Raga LLM Hub emphasizes these aspects. ### Is deepeval or raga-llm-hub more popular on GitHub? deepeval has more GitHub stars (17,226 vs 114). Stars measure visibility, not whether either tool fits your constraints. ### Are deepeval and raga-llm-hub open source? Yes - both are open-source projects on GitHub (deepeval: Apache-2.0, raga-llm-hub: Other). ### Where can I find alternatives to deepeval or raga-llm-hub? GraphCanon lists graph-backed alternatives at [deepeval alternatives](/tools/confident-ai-deepeval/alternatives) and [raga-llm-hub alternatives](/tools/raga-ai-hub-raga-llm-hub/alternatives) ([deepeval markdown twin](/tools/confident-ai-deepeval/alternatives.md), [raga-llm-hub markdown twin](/tools/raga-ai-hub-raga-llm-hub/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-raga-ai-hub-raga-llm-hub.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, deepeval or raga-llm-hub? deepeval: Very active. raga-llm-hub: 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 raga-llm-hub? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [deepeval trust report](/tools/confident-ai-deepeval/trust); [raga-llm-hub trust report](/tools/raga-ai-hub-raga-llm-hub/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/_