--- title: "guildai vs sacred" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/guildai-guildai-vs-idsia-sacred" tools: ["guildai-guildai", "idsia-sacred"] --- # guildai vs sacred *GraphCanon updated Aug 3, 2026* ## Verdict Pick guildai if guild AI is geared towards Python developers who need to manage various types of experiments and utilize optimization methods like grid search, random search, and Bayesian optimization; pick sacred if sacred is an experiment management tool for machine learning that emphasizes configuration management, logging, and reproducibility. [guildai](https://guild.ai) reports 904 GitHub stars, 93 forks, and 237 open issues, last pushed Apr 29, 2025. [sacred](https://github.com/IDSIA/sacred) has 4.4k stars, 393 forks, and 107 open issues, last pushed Oct 22, 2025. Figures are from public GitHub metadata via [guildai's repository](https://github.com/guildai/guildai) and [sacred's repository](https://github.com/IDSIA/sacred). | | [guildai](/tools/guildai-guildai.md) | [sacred](/tools/idsia-sacred.md) | | --- | --- | --- | | Tagline | Experiment tracking, ML developer tools | A tool for experiment configuration, logging, and reproducibility | | Stars | 904 | 4,372 | | Forks | 93 | 393 | | Open issues | 237 | 107 | | Language | Python | Python | | Adopt for | Guild AI is geared towards Python developers who need to manage various types of experiments and utilize optimization methods like grid search, random search, and Bayesian optimization. | Sacred is an experiment management tool for machine learning that emphasizes configuration management, logging, and reproducibility. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Sacred is open-source under the MIT license, providing broad permissiveness in its use and modification across various applications. | | Categories | Developer Tools, Model Training | Developer Tools, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [guildai](/tools/guildai-guildai.md) | [sacred](/tools/idsia-sacred.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 460d | 284d | | Open issues (now) | 237 | 107 | | Full report | [trust report](/tools/guildai-guildai/trust.md) | [trust report](/tools/idsia-sacred/trust.md) | ## Shared compatibility - **Python**: [guildai](/tools/guildai-guildai.md) - Python runtime; [sacred](/tools/idsia-sacred.md) - Python runtime ## Decision facts: guildai - **Adopt for:** Guild AI is geared towards Python developers who need to manage various types of experiments and utilize optimization methods like grid search, random search, and Bayesian optimization. ## Decision facts: sacred - **Pricing:** freemium - Being an open-source tool under the MIT license, Sacred can be used freely without any cost. - **Adopt for:** Sacred is an experiment management tool for machine learning that emphasizes configuration management, logging, and reproducibility. - **License detail:** Sacred is open-source under the MIT license, providing broad permissiveness in its use and modification across various applications. ## Choose when ### Choose guildai if… - License: guildai is Apache-2.0, sacred is MIT. - Tags unique to guildai: automation, bayesian-optimization, experiment tracking, grid search. - You require automation for running multiple experiment configurations to compare different models effectively. ### Choose sacred if… - License: sacred is MIT, guildai is Apache-2.0. - Pricing: Being an open-source tool under the MIT license, Sacred can be used freely without any cost.. - Tags unique to sacred: config injection, experiment management, logging, reproducibility. - When precise control over experiment configurations and their dependencies is required, allowing consistent reproduction of results. ## When NOT to use guildai - If your project exclusively uses languages other than Python for machine learning tasks, Guild AI's capabilities may not be fully leveraged due to language-specific functionalities. - Your model development does not require intricate optimization methods or trial automation provided by this toolkit. - The need for experimentation tracking and archiving on cloud solutions is limited or you prefer manual handling of experiment data. ## When NOT to use sacred - If your project does not require deep integration with MongoDB for logging purposes, as Sacred assumes this setup out-of-the-box without offering as much flexibility to other storage options. - When you need a tool with lightweight overhead, since Sacred's comprehensive feature set introduces more complexity suitable only for larger-scale projects. ## Common questions ### What is the difference between guildai and sacred? guildai: Experiment tracking, ML developer tools. sacred: A tool for experiment configuration, logging, and reproducibility. See the comparison table for live GitHub stats and shared categories. ### When should I choose guildai over sacred? Choose guildai over sacred when License: guildai is Apache-2.0, sacred is MIT; Tags unique to guildai: automation, bayesian-optimization, experiment tracking, grid search; You require automation for running multiple experiment configurations to compare different models effectively. ### When should I choose sacred over guildai? Choose sacred over guildai when License: sacred is MIT, guildai is Apache-2.0; Pricing: Being an open-source tool under the MIT license, Sacred can be used freely without any cost.; Tags unique to sacred: config injection, experiment management, logging, reproducibility; When precise control over experiment configurations and their dependencies is required, allowing consistent reproduction of results. ### When should I avoid guildai? If your project exclusively uses languages other than Python for machine learning tasks, Guild AI's capabilities may not be fully leveraged due to language-specific functionalities. Your model development does not require intricate optimization methods or trial automation provided by this toolkit. The need for experimentation tracking and archiving on cloud solutions is limited or you prefer manual handling of experiment data. ### When should I avoid sacred? If your project does not require deep integration with MongoDB for logging purposes, as Sacred assumes this setup out-of-the-box without offering as much flexibility to other storage options. When you need a tool with lightweight overhead, since Sacred's comprehensive feature set introduces more complexity suitable only for larger-scale projects. ### Is guildai or sacred more popular on GitHub? sacred has more GitHub stars (4,372 vs 904). Stars measure visibility, not whether either tool fits your constraints. ### Are guildai and sacred open source? Yes - both are open-source projects on GitHub (guildai: Apache-2.0, sacred: MIT). ### Where can I find alternatives to guildai or sacred? GraphCanon lists graph-backed alternatives at [guildai alternatives](/tools/guildai-guildai/alternatives) and [sacred alternatives](/tools/idsia-sacred/alternatives) ([guildai markdown twin](/tools/guildai-guildai/alternatives.md), [sacred markdown twin](/tools/idsia-sacred/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/guildai-guildai-vs-idsia-sacred.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, guildai or sacred? guildai: Dormant. sacred: 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 guildai and sacred? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [guildai trust report](/tools/guildai-guildai/trust); [sacred trust report](/tools/idsia-sacred/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=guildai-guildai`](/api/graphcanon/graph?tool=guildai-guildai) - 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/_