--- title: "athina-evals vs zeno" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/athina-ai-athina-evals-vs-zeno-ml-zeno" tools: ["athina-ai-athina-evals", "zeno-ml-zeno"] --- # athina-evals vs zeno *GraphCanon updated Aug 3, 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 zeno if zeno combines Python API with an interactive UI for evaluating ML models across various tasks. [athina-evals](https://docs.athina.ai) reports 301 GitHub stars, 22 forks, and 3 open issues, last pushed Jun 6, 2025. [zeno](https://zenoml.com) has 214 stars, 11 forks, and 45 open issues, last pushed Oct 5, 2023. Figures are from public GitHub metadata via [athina-evals's repository](https://github.com/athina-ai/athina-evals) and [zeno's repository](https://github.com/zeno-ml/zeno). | | [athina-evals](/tools/athina-ai-athina-evals.md) | [zeno](/tools/zeno-ml-zeno.md) | | --- | --- | --- | | Tagline | Python SDK for evaluating LLM generated responses | AI Data Management & Evaluation Platform | | Stars | 301 | 214 | | Forks | 22 | 11 | | Open issues | 3 | 45 | | Language | Python | Svelte | | Adopt for | athina-evals is a Python SDK developed for facilitating the evaluation of outputs from large language models through predefined metrics and frameworks. | Zeno combines Python API with an interactive UI for evaluating ML models across various tasks. | | Persona | - | - | | Runtime | - | - | | License | - | MIT | | 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) | [zeno](/tools/zeno-ml-zeno.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Archived (8%) | | Days since push | 417d | 1032d | | Archived on GitHub | No | Yes | | Open issues (now) | 3 | 45 | | Full report | [trust report](/tools/athina-ai-athina-evals/trust.md) | [trust report](/tools/zeno-ml-zeno/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: zeno - **Adopt for:** Zeno combines Python API with an interactive UI for evaluating ML models across various tasks. ## Choose when ### Choose athina-evals if… - athina-evals is primarily Python; zeno is Svelte. - Tags unique to athina-evals: evaluation, evaluation-metrics, llm-eval, llm-evaluation. - When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics ### Choose zeno if… - zeno is primarily Svelte; athina-evals is Python. - Tags unique to zeno: ai, data-science, machine-learning. - You need to analyze model performance interactively via a user interface ## 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 zeno - Your project requires real-time monitoring capabilities not provided by Zeno's evaluation framework - If you are looking for a specialized tool tailored only to specific data types, like just images or text without the modular versatility of Zeno ## Common questions ### What is the difference between athina-evals and zeno? athina-evals: Python SDK for evaluating LLM generated responses. zeno: AI Data Management & Evaluation Platform. See the comparison table for live GitHub stats and shared categories. ### When should I choose athina-evals over zeno? Choose athina-evals over zeno when athina-evals is primarily Python; zeno is Svelte; Tags unique to athina-evals: evaluation, evaluation-metrics, llm-eval, llm-evaluation; When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics. ### When should I choose zeno over athina-evals? Choose zeno over athina-evals when zeno is primarily Svelte; athina-evals is Python; Tags unique to zeno: ai, data-science, machine-learning; You need to analyze model performance interactively via a user interface. ### 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 zeno? Your project requires real-time monitoring capabilities not provided by Zeno's evaluation framework If you are looking for a specialized tool tailored only to specific data types, like just images or text without the modular versatility of Zeno ### Is athina-evals or zeno more popular on GitHub? athina-evals has more GitHub stars (301 vs 214). Stars measure visibility, not whether either tool fits your constraints. ### Are athina-evals and zeno open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to athina-evals or zeno? GraphCanon lists graph-backed alternatives at [athina-evals alternatives](/tools/athina-ai-athina-evals/alternatives) and [zeno alternatives](/tools/zeno-ml-zeno/alternatives) ([athina-evals markdown twin](/tools/athina-ai-athina-evals/alternatives.md), [zeno markdown twin](/tools/zeno-ml-zeno/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-zeno-ml-zeno.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, athina-evals or zeno? athina-evals: Dormant. zeno: Archived. 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 zeno? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [athina-evals trust report](/tools/athina-ai-athina-evals/trust); [zeno trust report](/tools/zeno-ml-zeno/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/_