Comparison
octoml-profile vs openpi
Verdict
Pick octoml-profile if octoML PyTorch Profiler provides profiling and acceleration tools for PyTorch models with remote execution capabilities; pick openpi if openpi is a repository for running AI models with specific GPU requirements for inference and fine-tuning, including LoRA and full fine-tuning modes.
Markdown twin · octoml-profile alternatives · openpi alternatives
GraphCanon updated Sep 30, 2026
10views this month
vs
Trust & integrity
| Signal | octoml-profile | openpi |
|---|---|---|
| Maintenance | Dormant (1254d since push) As of Sep 30, 2026 · github_public_v1 | Active (24d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 30, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 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
- octoml-profile
- Home for OctoML PyTorch Profiler
- openpi
- Repository for running AI models with GPU requirements specified for inference and fine-tuning.
Stars
- octoml-profile
- 113
- openpi
- 14k
Forks
- octoml-profile
- 10
- openpi
- 2.5k
Open issues
- octoml-profile
- 0
- openpi
- 345
Language
- octoml-profile
- -
- openpi
- Python
Adopt for
- octoml-profile
- OctoML PyTorch Profiler provides profiling and acceleration tools for PyTorch models with remote execution capabilities.
- openpi
- openpi is a repository for running AI models with specific GPU requirements for inference and fine-tuning, including LoRA and full fine-tuning modes.
Persona
- octoml-profile
- -
- openpi
- -
Runtime
- octoml-profile
- -
- openpi
- -
License
- octoml-profile
- Apache-2.0
- openpi
- Apache-2.0
Last pushed
- octoml-profile
- Apr 24, 2023
- openpi
- Aug 24, 2026
Categories
- octoml-profile
- Inference & Serving, Model Training
- openpi
- Inference & Serving, Model Training
Trust and health
Maintenance
- octoml-profile
- Dormant (18%)
- openpi
- Active (82%)
Days since push
- octoml-profile
- 1254d
- openpi
- 24d
Open issues (now)
- octoml-profile
- 0
- openpi
- 345
Stars delta
- octoml-profile
- 0 (30d)
- openpi
- +776 (30d)
Open issues delta
- octoml-profile
- 0 (30d)
- openpi
- +29 (30d)
Full report
- octoml-profile
- Trust report
- openpi
- Trust report
Choose octoml-profile if…
- Tags unique to octoml-profile: acceleration, performance optimization, profiling, pytorch.
- Need precise performance metrics on different backend architectures like CPU, GPU in cloud environments
- Leaner open-issue backlog (0).
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
Choose openpi if…
- Requirements: The repository requires an NVIDIA GPU with at least 8 GB of memory for inference, 22.5 GB for fine-tuning with LoRA, and 70 GB for full fine-tuning..
- Tags unique to openpi: fine-tuning, gpu, inference, lora.
- Use openpi when you need to run AI models with precise GPU memory requirements for inference and fine-tuning, particularly with LoRA and full fine-tuning modes.
When NOT to use openpi
- Avoid using openpi if your project requires multi-node training, as the current training script does not support this feature.
- Do not use openpi if you are working on an operating system other than Ubuntu 22.04, as the repository has not been tested with other systems.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- 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 (Physical-Intelligence/openpi) · observed Sep 20, 2026
- GitHub forks (Physical-Intelligence/openpi) · observed Sep 20, 2026
- Last push (Physical-Intelligence/openpi) · observed Aug 24, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: octoml-profile 113 · openpi 14k (synced Sep 30, 2026).
Common questions
- What is the difference between octoml-profile and openpi?
- octoml-profile: Home for OctoML PyTorch Profiler. openpi: Repository for running AI models with GPU requirements specified for inference and fine-tuning.. See the comparison table for live GitHub stats and shared categories.
- When should I choose octoml-profile over openpi?
- Choose octoml-profile over openpi when Tags unique to octoml-profile: acceleration, performance optimization, profiling, pytorch; Need precise performance metrics on different backend architectures like CPU, GPU in cloud environments; Leaner open-issue backlog (0).
- When should I choose openpi over octoml-profile?
- Choose openpi over octoml-profile when Requirements: The repository requires an NVIDIA GPU with at least 8 GB of memory for inference, 22.5 GB for fine-tuning with LoRA, and 70 GB for full fine-tuning.; Tags unique to openpi: fine-tuning, gpu, inference, lora; Use openpi when you need to run AI models with precise GPU memory requirements for inference and fine-tuning, particularly with LoRA and full fine-tuning modes.
- 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
- When should I avoid openpi?
- Avoid using openpi if your project requires multi-node training, as the current training script does not support this feature. Do not use openpi if you are working on an operating system other than Ubuntu 22.04, as the repository has not been tested with other systems.
- Is octoml-profile or openpi more popular on GitHub?
- openpi has more GitHub stars (13,874 vs 113). Stars measure visibility, not whether either tool fits your constraints.
- Are octoml-profile and openpi open source?
- Yes - both are open-source projects on GitHub (octoml-profile: Apache-2.0, openpi: Apache-2.0).
- Where can I find alternatives to octoml-profile or openpi?
- GraphCanon lists graph-backed alternatives at octoml-profile alternatives and openpi alternatives (octoml-profile markdown twin, openpi 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, octoml-profile or openpi?
- octoml-profile: Dormant. openpi: 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 octoml-profile and openpi?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: octoml-profile trust report; openpi trust report.