Home/Compare/RoBO vs hyperopt

Comparison

RoBO vs hyperopt

Verdict

Pick RoBO if roBO is a Python framework for robust Bayesian optimization using Gaussian processes and random forests; pick hyperopt if hyperopt offers distributed asynchronous hyperparameter optimization with multiple optimizers like TPE and Annealing.

Markdown twin · RoBO alternatives · hyperopt alternatives

GraphCanon updated 2w

RoBO logo

RoBO

automl/RoBO

492pushed Apr 30, 2019
vs
hyperopt logo

hyperopt

hyperopt/hyperopt

7.6kpushed Aug 3, 2026

Trust & integrity

SignalRoBOhyperopt
Maintenance
Dormant (2653d since push)
As of 2w · github_public_v1
Very active (0d since push)
As of 2w · github_public_v1
Provenance
Not a fork · Organization account
As of 2w · github_public_v1
Not a fork · Organization account
As of 2w · github_public_v1
OSV dependency advisories
Published findings
As of 1mo · osv@v1
No lockfile (source not queried)
As of 1mo · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

RoBO
A Robust Bayesian Optimization framework
hyperopt
Distributed Asynchronous Hyperparameter Optimization in Python

Stars

RoBO
492
hyperopt
7.6k

Forks

RoBO
129
hyperopt
1.1k

Open issues

RoBO
25
hyperopt
9

Language

RoBO
Python
hyperopt
Python

Adopt for

RoBO
RoBO is a Python framework for robust Bayesian optimization using Gaussian processes and random forests.
hyperopt
Hyperopt offers distributed asynchronous hyperparameter optimization with multiple optimizers like TPE and Annealing.

Persona

RoBO
-
hyperopt
-

Runtime

RoBO
-
hyperopt
-

License

RoBO
BSD-3-Clause
hyperopt
Other

Last pushed

RoBO
Apr 30, 2019
hyperopt
Aug 3, 2026

Categories

RoBO
Model Training
hyperopt
Model Training

Trust and health

Maintenance

RoBO
Dormant (18%)
hyperopt
Very active (96%)

Days since push

RoBO
2653d
hyperopt
0d

Open issues (now)

RoBO
25
hyperopt
9

OSV dependency advisories

RoBO
Published findings
hyperopt
No lockfile (source not queried)

Full report

hyperopt
Trust report

Shared compatibility

  • Python · RoBO: Python runtime · hyperopt: Python runtime

Choose RoBO if…

  • License: RoBO is BSD-3-Clause, hyperopt is Other.
  • Tags unique to RoBO: bayesian-optimization, gaussian processes, python, random forests.
  • For tasks requiring robust handling of noisy data in Bayesian Optimization

When NOT to use RoBO

  • Avoid if your project strictly requires open-source licenses other than BSD-3-Clause
  • Not suitable for users not comfortable installing external dependencies manually

Choose hyperopt if…

  • License: hyperopt is Other, RoBO is BSD-3-Clause.
  • Tags unique to hyperopt: annealing, asynchronous, distributed-computing, hyperparameter-optimization.
  • When you need to optimize machine learning model parameters on a distributed system asynchronously.

When NOT to use hyperopt

  • If your project does not support asynchronous execution, opting for synchronous tools might be more suitable.
  • Avoid if you prefer a simpler setup without the complexity of distributed systems and instead need straightforward hyperparameter tuning options.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: RoBO 492 · hyperopt 7.6k (synced Aug 4, 2026).

Common questions

What is the difference between RoBO and hyperopt?
RoBO: A Robust Bayesian Optimization framework. hyperopt: Distributed Asynchronous Hyperparameter Optimization in Python. See the comparison table for live GitHub stats and shared categories.
When should I choose RoBO over hyperopt?
Choose RoBO over hyperopt when License: RoBO is BSD-3-Clause, hyperopt is Other; Tags unique to RoBO: bayesian-optimization, gaussian processes, python, random forests; For tasks requiring robust handling of noisy data in Bayesian Optimization.
When should I choose hyperopt over RoBO?
Choose hyperopt over RoBO when License: hyperopt is Other, RoBO is BSD-3-Clause; Tags unique to hyperopt: annealing, asynchronous, distributed-computing, hyperparameter-optimization; When you need to optimize machine learning model parameters on a distributed system asynchronously.
When should I avoid RoBO?
Avoid if your project strictly requires open-source licenses other than BSD-3-Clause Not suitable for users not comfortable installing external dependencies manually
When should I avoid hyperopt?
If your project does not support asynchronous execution, opting for synchronous tools might be more suitable. Avoid if you prefer a simpler setup without the complexity of distributed systems and instead need straightforward hyperparameter tuning options.
Is RoBO or hyperopt more popular on GitHub?
hyperopt has more GitHub stars (7,598 vs 492). Stars measure visibility, not whether either tool fits your constraints.
Are RoBO and hyperopt open source?
Yes - both are open-source projects on GitHub (RoBO: BSD-3-Clause, hyperopt: Other).
Where can I find alternatives to RoBO or hyperopt?
GraphCanon lists graph-backed alternatives at RoBO alternatives and hyperopt alternatives (RoBO markdown twin, hyperopt markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, RoBO or hyperopt?
RoBO: Dormant. hyperopt: Very active. 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 RoBO and hyperopt?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: RoBO trust report; hyperopt trust report.

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