--- title: "autoai vs Spearmint" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/blobcity-autoai-vs-hips-spearmint" tools: ["blobcity-autoai", "hips-spearmint"] --- # autoai vs Spearmint *GraphCanon updated Aug 4, 2026* ## Verdict Pick autoai if python based framework for automated machine learning focused on numerical data, providing model search, hyper-parameter tuning, and Jupyter Notebook code generation; pick Spearmint if a specialized package for performing Bayesian optimization, Spearmint automates experiment running and parameter tuning to minimize objectives efficiently. [autoai](https://github.com/blobcity/autoai) reports 186 GitHub stars, 46 forks, and 9 open issues, last pushed Mar 25, 2025. [Spearmint](https://github.com/HIPS/Spearmint) has 1.6k stars, 327 forks, and 77 open issues, last pushed Dec 27, 2019. Figures are from public GitHub metadata via [autoai's repository](https://github.com/blobcity/autoai) and [Spearmint's repository](https://github.com/HIPS/Spearmint). | | [autoai](/tools/blobcity-autoai.md) | [Spearmint](/tools/hips-spearmint.md) | | --- | --- | --- | | Tagline | Python based framework for Automatic AI enabling model search, hyper-parameter tuning and Jupyter Notebook code generation | Bayesian optimization codebase | | Stars | 186 | 1,573 | | Forks | 46 | 327 | | Open issues | 9 | 77 | | Language | Python | Python | | Adopt for | Python based framework for automated machine learning focused on numerical data, providing model search, hyper-parameter tuning, and Jupyter Notebook code generation. | A specialized package for performing Bayesian optimization, Spearmint automates experiment running and parameter tuning to minimize objectives efficiently. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Other | | Categories | Model Training | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [autoai](/tools/blobcity-autoai.md) | [Spearmint](/tools/hips-spearmint.md) | | --- | --- | --- | | Days since push | 496d | 2411d | | Open issues (now) | 9 | 77 | | Full report | [trust report](/tools/blobcity-autoai/trust.md) | [trust report](/tools/hips-spearmint/trust.md) | ## Shared compatibility - **Python**: [autoai](/tools/blobcity-autoai.md) - Python runtime; [Spearmint](/tools/hips-spearmint.md) - Python runtime ## Decision facts: autoai - **Adopt for:** Python based framework for automated machine learning focused on numerical data, providing model search, hyper-parameter tuning, and Jupyter Notebook code generation. ## Decision facts: Spearmint - **Adopt for:** A specialized package for performing Bayesian optimization, Spearmint automates experiment running and parameter tuning to minimize objectives efficiently. ## Choose when ### Choose autoai if… - License: autoai is Apache-2.0, Spearmint is Other. - Tags unique to autoai: ai, autoai, automl, codegen. - Use AutoAI when you need a tool that can handle both regression and classification tasks specifically over numerical datasets. ### Choose Spearmint if… - License: Spearmint is Other, autoai is Apache-2.0. - Tags unique to Spearmint: automated-experimentation, bayesian-optimization, hyperparameter-tuning. - - When you require automated experimentation with parameters that can be iteratively adjusted ## When NOT to use autoai - Avoid using AutoAI if your dataset includes non-numerical data exclusively as the framework is tailored for numerical data processing. - Do not use if generating model training scripts in formats other than Jupyter Notebooks is required, as this tool only supports Python code output within a Jupyter format. ## When NOT to use Spearmint - - If your project requires a permissive license as Spearmint operates under an Academic and Non-Commercial Research Use License - - If you need real-time or continuous parameter tuning outside of batch experimentation contexts as Spearmint is suited for controlled experiment setups ## Common questions ### What is the difference between autoai and Spearmint? autoai: Python based framework for Automatic AI enabling model search, hyper-parameter tuning and Jupyter Notebook code generation. Spearmint: Bayesian optimization codebase. See the comparison table for live GitHub stats and shared categories. ### When should I choose autoai over Spearmint? Choose autoai over Spearmint when License: autoai is Apache-2.0, Spearmint is Other; Tags unique to autoai: ai, autoai, automl, codegen; Use AutoAI when you need a tool that can handle both regression and classification tasks specifically over numerical datasets. ### When should I choose Spearmint over autoai? Choose Spearmint over autoai when License: Spearmint is Other, autoai is Apache-2.0; Tags unique to Spearmint: automated-experimentation, bayesian-optimization, hyperparameter-tuning; - When you require automated experimentation with parameters that can be iteratively adjusted. ### When should I avoid autoai? Avoid using AutoAI if your dataset includes non-numerical data exclusively as the framework is tailored for numerical data processing. Do not use if generating model training scripts in formats other than Jupyter Notebooks is required, as this tool only supports Python code output within a Jupyter format. ### When should I avoid Spearmint? - If your project requires a permissive license as Spearmint operates under an Academic and Non-Commercial Research Use License - If you need real-time or continuous parameter tuning outside of batch experimentation contexts as Spearmint is suited for controlled experiment setups ### Is autoai or Spearmint more popular on GitHub? Spearmint has more GitHub stars (1,573 vs 186). Stars measure visibility, not whether either tool fits your constraints. ### Are autoai and Spearmint open source? Yes - both are open-source projects on GitHub (autoai: Apache-2.0, Spearmint: Other). ### Where can I find alternatives to autoai or Spearmint? GraphCanon lists graph-backed alternatives at [autoai alternatives](/tools/blobcity-autoai/alternatives) and [Spearmint alternatives](/tools/hips-spearmint/alternatives) ([autoai markdown twin](/tools/blobcity-autoai/alternatives.md), [Spearmint markdown twin](/tools/hips-spearmint/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/blobcity-autoai-vs-hips-spearmint.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, autoai or Spearmint? autoai: Dormant. Spearmint: 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 autoai and Spearmint? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [autoai trust report](/tools/blobcity-autoai/trust); [Spearmint trust report](/tools/hips-spearmint/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=blobcity-autoai`](/api/graphcanon/graph?tool=blobcity-autoai) - 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/_