Comparison
octo vs octoml-profile
Verdict
Pick octo if octo is a transformer-based robot policy trained on 800k robot trajectories, offering support for CPU, GPU, and TPU installations; pick octoml-profile if octoML PyTorch Profiler provides profiling and acceleration tools for PyTorch models with remote execution capabilities.
Markdown twin · octo alternatives · octoml-profile alternatives
GraphCanon updated Sep 30, 2026
6views this month
vs
Trust & integrity
| Signal | octo | octoml-profile |
|---|---|---|
| Maintenance | Dormant (779d since push) As of Sep 18, 2026 · github_public_v1 | Dormant (1254d since push) As of Sep 30, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 30, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Sep 18, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · 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
- octo
- Transformer-based robot policy trained on 800k robot trajectories
- octoml-profile
- Home for OctoML PyTorch Profiler
Stars
- octo
- 1.8k
- octoml-profile
- 113
Forks
- octo
- 280
- octoml-profile
- 10
Open issues
- octo
- 96
- octoml-profile
- 0
Language
- octo
- Python
- octoml-profile
- -
Adopt for
- octo
- Octo is a transformer-based robot policy trained on 800k robot trajectories, offering support for CPU, GPU, and TPU installations.
- octoml-profile
- OctoML PyTorch Profiler provides profiling and acceleration tools for PyTorch models with remote execution capabilities.
Persona
- octo
- -
- octoml-profile
- -
Runtime
- octo
- -
- octoml-profile
- -
License
- octo
- MIT
- octoml-profile
- Apache-2.0
Last pushed
- octo
- Jul 31, 2024
- octoml-profile
- Apr 24, 2023
Categories
- octo
- Model Training
- octoml-profile
- Inference & Serving, Model Training
Trust and health
Days since push
- octo
- 779d
- octoml-profile
- 1254d
Open issues (now)
- octo
- 96
- octoml-profile
- 0
Stars delta
- octo
- +56 (30d)
- octoml-profile
- 0 (30d)
OSV dependency advisories
- octo
- Published findings
- octoml-profile
- No lockfile (source not queried)
Full report
- octo
- Trust report
- octoml-profile
- Trust report
Shared compatibility
- Python · octo: Python runtime · octoml-profile: Python runtime
Choose octo if…
- License: octo is MIT, octoml-profile is Apache-2.0.
- Requirements: Installation requires setting up a Python 3.10 environment with Conda.; For GPU support, Jax with CUDA 11 is required.; For TPU support, Jax with TPU support is required..
- Tags unique to octo: finetuning, gpu, jax, robotics.
- Use Octo when you need a transformer-based policy for robot control tasks that can leverage a large dataset of 800k robot trajectories.
When NOT to use octo
- Avoid Octo if your project does not require the scale of data it was trained on, as the model might be overkill for smaller datasets.
- Do not use Octo if you are working in an environment that does not support Python or the specific versions of Jax required for GPU and TPU support.
- If your project has strict licensing requirements that do not allow for MIT-licensed software, Octo would not be a suitable choice.
Choose octoml-profile if…
- License: octoml-profile is Apache-2.0, octo is MIT.
- Tags unique to octoml-profile: acceleration, performance optimization, profiling, pytorch.
- Also covers Inference & Serving.
- Need precise performance metrics on different backend architectures like CPU, GPU in cloud environments
When NOT to use octoml-profile
- Development for local, offline usage only without remote profiling needs
- Working with PyTorch versions below 2.0 or incompatible with specific CUDA/Apple silicon versions outlined in installation guide
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (octo-models/octo) · observed Sep 20, 2026
- GitHub forks (octo-models/octo) · observed Sep 20, 2026
- Last push (octo-models/octo) · observed Jul 31, 2024
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (octoml/octoml-profile) · observed Sep 30, 2026
- GitHub forks (octoml/octoml-profile) · observed Sep 30, 2026
- Last push (octoml/octoml-profile) · observed Apr 24, 2023
- License file (Apache-2.0) · observed Sep 30, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: octo 1.8k · octoml-profile 113 (synced Sep 20, 2026).
Common questions
- What is the difference between octo and octoml-profile?
- octo: Transformer-based robot policy trained on 800k robot trajectories. octoml-profile: Home for OctoML PyTorch Profiler. See the comparison table for live GitHub stats and shared categories.
- When should I choose octo over octoml-profile?
- Choose octo over octoml-profile when License: octo is MIT, octoml-profile is Apache-2.0; Requirements: Installation requires setting up a Python 3.10 environment with Conda.; For GPU support, Jax with CUDA 11 is required.; For TPU support, Jax with TPU support is required.; Tags unique to octo: finetuning, gpu, jax, robotics; Use Octo when you need a transformer-based policy for robot control tasks that can leverage a large dataset of 800k robot trajectories.
- When should I choose octoml-profile over octo?
- Choose octoml-profile over octo when License: octoml-profile is Apache-2.0, octo is MIT; Tags unique to octoml-profile: acceleration, performance optimization, profiling, pytorch; Also covers Inference & Serving; Need precise performance metrics on different backend architectures like CPU, GPU in cloud environments.
- When should I avoid octo?
- Avoid Octo if your project does not require the scale of data it was trained on, as the model might be overkill for smaller datasets. Do not use Octo if you are working in an environment that does not support Python or the specific versions of Jax required for GPU and TPU support. If your project has strict licensing requirements that do not allow for MIT-licensed software, Octo would not be a suitable choice.
- When should I avoid octoml-profile?
- Development for local, offline usage only without remote profiling needs Working with PyTorch versions below 2.0 or incompatible with specific CUDA/Apple silicon versions outlined in installation guide
- Is octo or octoml-profile more popular on GitHub?
- octo has more GitHub stars (1,778 vs 113). Stars measure visibility, not whether either tool fits your constraints.
- Are octo and octoml-profile open source?
- Yes - both are open-source projects on GitHub (octo: MIT, octoml-profile: Apache-2.0).
- Where can I find alternatives to octo or octoml-profile?
- GraphCanon lists graph-backed alternatives at octo alternatives and octoml-profile alternatives (octo markdown twin, octoml-profile 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, octo or octoml-profile?
- octo: Dormant. octoml-profile: 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 octo and octoml-profile?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: octo trust report; octoml-profile trust report.