--- title: "Auto-PyTorch vs Spearmint" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/automl-auto-pytorch-vs-hips-spearmint" tools: ["automl-auto-pytorch", "hips-spearmint"] --- # Auto-PyTorch vs Spearmint *GraphCanon updated Aug 4, 2026* ## Verdict Pick Auto-PyTorch if auto-PyTorch specializes in automatic architecture search and hyperparameter optimization for deep-learning models using PyTorch; pick Spearmint if a specialized package for performing Bayesian optimization, Spearmint automates experiment running and parameter tuning to minimize objectives efficiently. [Auto-PyTorch](https://github.com/automl/Auto-PyTorch) reports 2.5k GitHub stars, 303 forks, and 75 open issues, last pushed Apr 9, 2024. [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 [Auto-PyTorch's repository](https://github.com/automl/Auto-PyTorch) and [Spearmint's repository](https://github.com/HIPS/Spearmint). | | [Auto-PyTorch](/tools/automl-auto-pytorch.md) | [Spearmint](/tools/hips-spearmint.md) | | --- | --- | --- | | Tagline | Automatic architecture search and hyperparameter optimization for PyTorch | Bayesian optimization codebase | | Stars | 2,541 | 1,573 | | Forks | 303 | 327 | | Open issues | 75 | 77 | | Language | Python | Python | | Adopt for | Auto-PyTorch specializes in automatic architecture search and hyperparameter optimization for deep-learning models using PyTorch. | 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 | Data & Retrieval, Model Training | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Auto-PyTorch](/tools/automl-auto-pytorch.md) | [Spearmint](/tools/hips-spearmint.md) | | --- | --- | --- | | Days since push | 846d | 2411d | | Open issues (now) | 75 | 77 | | Full report | [trust report](/tools/automl-auto-pytorch/trust.md) | [trust report](/tools/hips-spearmint/trust.md) | ## Shared compatibility - **Python**: [Auto-PyTorch](/tools/automl-auto-pytorch.md) - Python runtime; [Spearmint](/tools/hips-spearmint.md) - Python runtime ## Decision facts: Auto-PyTorch - **Adopt for:** Auto-PyTorch specializes in automatic architecture search and hyperparameter optimization for deep-learning models using PyTorch. ## 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 Auto-PyTorch if… - License: Auto-PyTorch is Apache-2.0, Spearmint is Other. - Tags unique to Auto-PyTorch: automl, deep-learning, pytorch, tabular-data. - Also covers Data & Retrieval. - Auto-PyTorch ships Docker support for self-hosted deployment. - Use when you need to automate both architectural searches and hyperparameter tuning specifically for PyTorch-based deep learning models. ### Choose Spearmint if… - License: Spearmint is Other, Auto-PyTorch 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 Auto-PyTorch - Avoid using it if your AI development focuses on frameworks other than PyTorch. - Do not use when the requirements do not involve deep learning models or you are not interested in automating architecture search and hyperparameter tuning. ## 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 Auto-PyTorch and Spearmint? Auto-PyTorch: Automatic architecture search and hyperparameter optimization for PyTorch. Spearmint: Bayesian optimization codebase. See the comparison table for live GitHub stats and shared categories. ### When should I choose Auto-PyTorch over Spearmint? Choose Auto-PyTorch over Spearmint when License: Auto-PyTorch is Apache-2.0, Spearmint is Other; Tags unique to Auto-PyTorch: automl, deep-learning, pytorch, tabular-data; Also covers Data & Retrieval; Auto-PyTorch ships Docker support for self-hosted deployment; Use when you need to automate both architectural searches and hyperparameter tuning specifically for PyTorch-based deep learning models. ### When should I choose Spearmint over Auto-PyTorch? Choose Spearmint over Auto-PyTorch when License: Spearmint is Other, Auto-PyTorch 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 Auto-PyTorch? Avoid using it if your AI development focuses on frameworks other than PyTorch. Do not use when the requirements do not involve deep learning models or you are not interested in automating architecture search and hyperparameter tuning. ### 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 Auto-PyTorch or Spearmint more popular on GitHub? Auto-PyTorch has more GitHub stars (2,541 vs 1,573). Stars measure visibility, not whether either tool fits your constraints. ### Are Auto-PyTorch and Spearmint open source? Yes - both are open-source projects on GitHub (Auto-PyTorch: Apache-2.0, Spearmint: Other). ### Where can I find alternatives to Auto-PyTorch or Spearmint? GraphCanon lists graph-backed alternatives at [Auto-PyTorch alternatives](/tools/automl-auto-pytorch/alternatives) and [Spearmint alternatives](/tools/hips-spearmint/alternatives) ([Auto-PyTorch markdown twin](/tools/automl-auto-pytorch/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/automl-auto-pytorch-vs-hips-spearmint.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Auto-PyTorch or Spearmint? Auto-PyTorch: 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 Auto-PyTorch and Spearmint? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Auto-PyTorch trust report](/tools/automl-auto-pytorch/trust); [Spearmint trust report](/tools/hips-spearmint/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=automl-auto-pytorch`](/api/graphcanon/graph?tool=automl-auto-pytorch) - 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/_