--- title: "dingo vs zeno" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/migoxlab-dingo-vs-zeno-ml-zeno" tools: ["migoxlab-dingo", "zeno-ml-zeno"] --- # dingo vs zeno *GraphCanon updated Aug 7, 2026* ## Verdict Pick dingo if dingo includes a unique focus on multi-agent debate patterns ('Agent-as-a-Judge') for bias reduction and complex reasoning in evaluation tasks; pick zeno if zeno combines Python API with an interactive UI for evaluating ML models across various tasks. [dingo](https://dingo.openxlab.org.cn/) reports 733 GitHub stars, 74 forks, and 4 open issues, last pushed Aug 6, 2026. [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 [dingo's repository](https://github.com/MigoXLab/dingo) and [zeno's repository](https://github.com/zeno-ml/zeno). | | [dingo](/tools/migoxlab-dingo.md) | [zeno](/tools/zeno-ml-zeno.md) | | --- | --- | --- | | Tagline | Dingo: A Comprehensive AI Data, Model and Application Quality Evaluation Tool | AI Data Management & Evaluation Platform | | Stars | 733 | 214 | | Forks | 74 | 11 | | Open issues | 4 | 45 | | Language | Python | Svelte | | Adopt for | Dingo includes a unique focus on multi-agent debate patterns ('Agent-as-a-Judge') for bias reduction and complex reasoning in evaluation tasks. | Zeno combines Python API with an interactive UI for evaluating ML models across various tasks. | | Persona | - | - | | Runtime | - | - | | License | Licensed under the Apache-2.0 license, it includes fasttext functionality for language detection, which itself is licensed under the MIT License. | MIT | | Categories | Data & Retrieval, Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [dingo](/tools/migoxlab-dingo.md) | [zeno](/tools/zeno-ml-zeno.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Archived (8%) | | Days since push | 0d | 1032d | | Archived on GitHub | No | Yes | | Open issues (now) | 4 | 45 | | Full report | [trust report](/tools/migoxlab-dingo/trust.md) | [trust report](/tools/zeno-ml-zeno/trust.md) | ## Decision facts: dingo - **Pricing:** freemium - The tool currently offers free open-source options under an Apache 2.0 license with plans for future SaaS platform services that may come at a cost. - **Adopt for:** Dingo includes a unique focus on multi-agent debate patterns ('Agent-as-a-Judge') for bias reduction and complex reasoning in evaluation tasks. - **License detail:** Licensed under the Apache-2.0 license, it includes fasttext functionality for language detection, which itself is licensed under the MIT License. ## Decision facts: zeno - **Adopt for:** Zeno combines Python API with an interactive UI for evaluating ML models across various tasks. ## Choose when ### Choose dingo if… - dingo is primarily Python; zeno is Svelte. - License: dingo is Apache-2.0, zeno is MIT. - Pricing: The tool currently offers free open-source options under an Apache 2.0 license with plans for future SaaS platform services that may come at a cost.. - Tags unique to dingo: agent-as-a-judge, data-evaluation, data-quality, hallucination-detection. - Also covers Data & Retrieval. - When evaluating the quality of data, models, or applications that require insights from multiple perspectives to detect nuances such as bias or hallucination. ### Choose zeno if… - zeno is primarily Svelte; dingo is Python. - License: zeno is MIT, dingo is Apache-2.0. - Tags unique to zeno: ai, data-science, evaluation-framework, machine-learning. - You need to analyze model performance interactively via a user interface ## When NOT to use dingo - If your project does not benefit from a multi-agent approach for evaluation, and simpler single-model approaches suffice. - In scenarios where immediate feedback is critical but Dingo's planned SaaS platform with API access and dashboard support are still under development. ## 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 dingo and zeno? dingo: Dingo: A Comprehensive AI Data, Model and Application Quality Evaluation Tool. zeno: AI Data Management & Evaluation Platform. See the comparison table for live GitHub stats and shared categories. ### When should I choose dingo over zeno? Choose dingo over zeno when dingo is primarily Python; zeno is Svelte; License: dingo is Apache-2.0, zeno is MIT; Pricing: The tool currently offers free open-source options under an Apache 2.0 license with plans for future SaaS platform services that may come at a cost.; Tags unique to dingo: agent-as-a-judge, data-evaluation, data-quality, hallucination-detection; Also covers Data & Retrieval; When evaluating the quality of data, models, or applications that require insights from multiple perspectives to detect nuances such as bias or hallucination. ### When should I choose zeno over dingo? Choose zeno over dingo when zeno is primarily Svelte; dingo is Python; License: zeno is MIT, dingo is Apache-2.0; Tags unique to zeno: ai, data-science, evaluation-framework, machine-learning; You need to analyze model performance interactively via a user interface. ### When should I avoid dingo? If your project does not benefit from a multi-agent approach for evaluation, and simpler single-model approaches suffice. In scenarios where immediate feedback is critical but Dingo's planned SaaS platform with API access and dashboard support are still under development. ### 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 dingo or zeno more popular on GitHub? dingo has more GitHub stars (733 vs 214). Stars measure visibility, not whether either tool fits your constraints. ### Are dingo and zeno open source? Yes - both are open-source projects on GitHub (dingo: Apache-2.0, zeno: MIT). ### Where can I find alternatives to dingo or zeno? GraphCanon lists graph-backed alternatives at [dingo alternatives](/tools/migoxlab-dingo/alternatives) and [zeno alternatives](/tools/zeno-ml-zeno/alternatives) ([dingo markdown twin](/tools/migoxlab-dingo/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/migoxlab-dingo-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, dingo or zeno? dingo: Very active. 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 dingo and zeno? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [dingo trust report](/tools/migoxlab-dingo/trust); [zeno trust report](/tools/zeno-ml-zeno/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=migoxlab-dingo`](/api/graphcanon/graph?tool=migoxlab-dingo) - 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/_