--- title: "octo vs octoml-profile" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/octo-models-octo-vs-octoml-octoml-profile" tools: ["octo-models-octo", "octoml-octoml-profile"] --- # octo vs octoml-profile *GraphCanon updated Sep 30, 2026* ## 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. [octo](https://octo-models.github.io/) reports 1.8k GitHub stars, 280 forks, and 96 open issues, last pushed Jul 31, 2024. [octoml-profile](https://github.com/octoml/octoml-profile) has 113 stars, 10 forks, and 0 open issues, last pushed Apr 24, 2023. Figures are from public GitHub metadata via [octo's repository](https://github.com/octo-models/octo) and [octoml-profile's repository](https://github.com/octoml/octoml-profile). | | [octo](/tools/octo-models-octo.md) | [octoml-profile](/tools/octoml-octoml-profile.md) | | --- | --- | --- | | Tagline | Transformer-based robot policy trained on 800k robot trajectories | Home for OctoML PyTorch Profiler | | Stars | 1,778 | 113 | | Forks | 280 | 10 | | Open issues | 96 | 0 | | Language | Python | - | | Adopt for | Octo is a transformer-based robot policy trained on 800k robot trajectories, offering support for CPU, GPU, and TPU installations. | OctoML PyTorch Profiler provides profiling and acceleration tools for PyTorch models with remote execution capabilities. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Model Training | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [octo](/tools/octo-models-octo.md) | [octoml-profile](/tools/octoml-octoml-profile.md) | | --- | --- | --- | | Days since push | 779d | 1254d | | Open issues (now) | 96 | 0 | | Stars delta | +56 (30d) | 0 (30d) | | Full report | [trust report](/tools/octo-models-octo/trust.md) | [trust report](/tools/octoml-octoml-profile/trust.md) | ## Shared compatibility - **Python**: [octo](/tools/octo-models-octo.md) - Python runtime; [octoml-profile](/tools/octoml-octoml-profile.md) - Python runtime ## Decision facts: octo - **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. - **Adopt for:** Octo is a transformer-based robot policy trained on 800k robot trajectories, offering support for CPU, GPU, and TPU installations. ## Decision facts: octoml-profile - **Adopt for:** OctoML PyTorch Profiler provides profiling and acceleration tools for PyTorch models with remote execution capabilities. ## Choose when ### 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. ### 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 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 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 ## 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](/tools/octo-models-octo/alternatives) and [octoml-profile alternatives](/tools/octoml-octoml-profile/alternatives) ([octo markdown twin](/tools/octo-models-octo/alternatives.md), [octoml-profile markdown twin](/tools/octoml-octoml-profile/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/octo-models-octo-vs-octoml-octoml-profile.md) 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](/tools/octo-models-octo/trust); [octoml-profile trust report](/tools/octoml-octoml-profile/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=octo-models-octo`](/api/graphcanon/graph?tool=octo-models-octo) - 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/_