--- title: "athina-evals vs ragas" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/athina-ai-athina-evals-vs-vibrantlabsai-ragas" tools: ["athina-ai-athina-evals", "vibrantlabsai-ragas"] --- # athina-evals vs ragas *GraphCanon updated Sep 20, 2026* ## Verdict Pick athina-evals if athina-evals is a Python SDK developed for facilitating the evaluation of outputs from large language models through predefined metrics and frameworks; pick ragas if ragas is a Python-based tool designed to enhance the evaluation process of Large Language Model (LLM) applications through specialized workflows and performance insights. [athina-evals](https://docs.athina.ai) reports 301 GitHub stars, 22 forks, and 4 open issues, last pushed Jun 6, 2025. [ragas](https://docs.ragas.io) has 16k stars, 1.7k forks, and 601 open issues, last pushed Feb 24, 2026. Figures are from public GitHub metadata via [athina-evals's repository](https://github.com/athina-ai/athina-evals) and [ragas's repository](https://github.com/vibrantlabsai/ragas). | | [athina-evals](/tools/athina-ai-athina-evals.md) | [ragas](/tools/vibrantlabsai-ragas.md) | | --- | --- | --- | | Tagline | Python SDK for evaluating LLM generated responses | Supercharge Your LLM Application Evaluations 🚀 | | Stars | 301 | 15,783 | | Forks | 22 | 1,712 | | Open issues | 4 | 601 | | Language | Python | Python | | Adopt for | athina-evals is a Python SDK developed for facilitating the evaluation of outputs from large language models through predefined metrics and frameworks. | Ragas is a Python-based tool designed to enhance the evaluation process of Large Language Model (LLM) applications through specialized workflows and performance insights. | | Persona | - | developer harness | | Runtime | - | - | | License | - | Apache-2.0 | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [athina-evals](/tools/athina-ai-athina-evals.md) | [ragas](/tools/vibrantlabsai-ragas.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 470d | 207d | | Open issues (now) | 4 | 601 | | Stars delta | 0 (30d) | +395 (30d) | | Open issues delta | +1 (30d) | +39 (30d) | | Full report | [trust report](/tools/athina-ai-athina-evals/trust.md) | [trust report](/tools/vibrantlabsai-ragas/trust.md) | ## Decision facts: athina-evals - **Adopt for:** athina-evals is a Python SDK developed for facilitating the evaluation of outputs from large language models through predefined metrics and frameworks. ## Decision facts: ragas - **Requirements:** Min 4 GB RAM - **Adopt for:** Ragas is a Python-based tool designed to enhance the evaluation process of Large Language Model (LLM) applications through specialized workflows and performance insights. - **Persona:** developer harness ## Choose when ### Choose athina-evals if… - Tags unique to athina-evals: evaluation-framework, evaluation-metrics, llm-eval, llm-evaluation. - When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics - Leaner open-issue backlog (4). ### Choose ragas if… - Requirements: Min 4 GB RAM. - Tags unique to ragas: llm, llmops. - When you need advanced tools tailored for evaluating LLM applications, as RAGAS offers specific optimizations not found in generic testing frameworks. ## When NOT to use athina-evals - If open-source alternatives with transparent customization options are preferred over athina-evals' approach - In scenarios where API access requirements limit the ability to perform evaluations offline or in private environments ## When NOT to use ragas - If your application does not involve Large Language Models or if the evaluation needs are basic; RAGAS is optimized for LLM-specific evaluations which may be overkill for simpler systems. - For projects that require real-time monitoring or continuous testing of live models where more dynamic observability tools might offer better support. ## Common questions ### What is the difference between athina-evals and ragas? athina-evals: Python SDK for evaluating LLM generated responses. ragas: Supercharge Your LLM Application Evaluations 🚀. See the comparison table for live GitHub stats and shared categories. ### When should I choose athina-evals over ragas? Choose athina-evals over ragas when Tags unique to athina-evals: evaluation-framework, evaluation-metrics, llm-eval, llm-evaluation; When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics; Leaner open-issue backlog (4). ### When should I choose ragas over athina-evals? Choose ragas over athina-evals when Requirements: Min 4 GB RAM; Tags unique to ragas: llm, llmops; When you need advanced tools tailored for evaluating LLM applications, as RAGAS offers specific optimizations not found in generic testing frameworks. ### When should I avoid athina-evals? If open-source alternatives with transparent customization options are preferred over athina-evals' approach In scenarios where API access requirements limit the ability to perform evaluations offline or in private environments ### When should I avoid ragas? If your application does not involve Large Language Models or if the evaluation needs are basic; RAGAS is optimized for LLM-specific evaluations which may be overkill for simpler systems. For projects that require real-time monitoring or continuous testing of live models where more dynamic observability tools might offer better support. ### Is athina-evals or ragas more popular on GitHub? ragas has more GitHub stars (15,783 vs 301). Stars measure visibility, not whether either tool fits your constraints. ### Are athina-evals and ragas open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to athina-evals or ragas? GraphCanon lists graph-backed alternatives at [athina-evals alternatives](/tools/athina-ai-athina-evals/alternatives) and [ragas alternatives](/tools/vibrantlabsai-ragas/alternatives) ([athina-evals markdown twin](/tools/athina-ai-athina-evals/alternatives.md), [ragas markdown twin](/tools/vibrantlabsai-ragas/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/athina-ai-athina-evals-vs-vibrantlabsai-ragas.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, athina-evals or ragas? athina-evals: Dormant. ragas: Slowing. 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 athina-evals and ragas? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [athina-evals trust report](/tools/athina-ai-athina-evals/trust); [ragas trust report](/tools/vibrantlabsai-ragas/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=athina-ai-athina-evals`](/api/graphcanon/graph?tool=athina-ai-athina-evals) - 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/_