--- title: "accelerate vs octoml-profile" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/huggingface-accelerate-vs-octoml-octoml-profile" tools: ["huggingface-accelerate", "octoml-octoml-profile"] --- # accelerate vs octoml-profile *GraphCanon updated Aug 4, 2026* ## Verdict Pick accelerate if tool: accelerate; pick octoml-profile if octoML PyTorch Profiler provides profiling and acceleration tools for PyTorch models with remote execution capabilities. [accelerate](https://huggingface.co/docs/accelerate) reports 9.8k GitHub stars, 1.4k forks, and 105 open issues, last pushed Jul 30, 2026. [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 [accelerate's repository](https://github.com/huggingface/accelerate) and [octoml-profile's repository](https://github.com/octoml/octoml-profile). | | [accelerate](/tools/huggingface-accelerate.md) | [octoml-profile](/tools/octoml-octoml-profile.md) | | --- | --- | --- | | Tagline | A tool for launching, training, and using PyTorch models with ease on various devices, configurations, including mixed precision support. | Home for OctoML PyTorch Profiler | | Stars | 9,803 | 113 | | Forks | 1,425 | 10 | | Open issues | 105 | 0 | | Language | Python | - | | Adopt for | Tool: accelerate | OctoML PyTorch Profiler provides profiling and acceleration tools for PyTorch models with remote execution capabilities. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Inference & Serving, Model Training | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [accelerate](/tools/huggingface-accelerate.md) | [octoml-profile](/tools/octoml-octoml-profile.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 3d | 1197d | | Open issues (now) | 105 | 0 | | Full report | [trust report](/tools/huggingface-accelerate/trust.md) | [trust report](/tools/octoml-octoml-profile/trust.md) | ## Shared compatibility - **Python**: [accelerate](/tools/huggingface-accelerate.md) - Python runtime; [octoml-profile](/tools/octoml-octoml-profile.md) - Python runtime ## Decision facts: accelerate - **Adopt for:** Tool: accelerate ## Decision facts: octoml-profile - **Adopt for:** OctoML PyTorch Profiler provides profiling and acceleration tools for PyTorch models with remote execution capabilities. ## Choose when ### Choose accelerate if… - Tags unique to accelerate: deepspeed, fsdp, mixed precision. - Easy mixed-precision support for PyTorch models - More GitHub stars (9.8k vs 113) - visibility, not fit. ### Choose octoml-profile if… - Tags unique to octoml-profile: acceleration, performance optimization, profiling. - Need precise performance metrics on different backend architectures like CPU, GPU in cloud environments - Leaner open-issue backlog (0). ## When NOT to use accelerate - Non-PyTorch projects do not benefit from this tool - Doesnt offer advanced auto-tuning features for other frameworks like TensorFlow - Limited to Python environments compatible with PyTorch 1.10.0+ ## 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 ## Common questions ### What is the difference between accelerate and octoml-profile? accelerate: A tool for launching, training, and using PyTorch models with ease on various devices, configurations, including mixed precision support.. octoml-profile: Home for OctoML PyTorch Profiler. See the comparison table for live GitHub stats and shared categories. ### When should I choose accelerate over octoml-profile? Choose accelerate over octoml-profile when Tags unique to accelerate: deepspeed, fsdp, mixed precision; Easy mixed-precision support for PyTorch models; More GitHub stars (9.8k vs 113) - visibility, not fit. ### When should I choose octoml-profile over accelerate? Choose octoml-profile over accelerate when Tags unique to octoml-profile: acceleration, performance optimization, profiling; Need precise performance metrics on different backend architectures like CPU, GPU in cloud environments; Leaner open-issue backlog (0). ### When should I avoid accelerate? Non-PyTorch projects do not benefit from this tool Doesnt offer advanced auto-tuning features for other frameworks like TensorFlow Limited to Python environments compatible with PyTorch 1.10.0+ ### 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 accelerate or octoml-profile more popular on GitHub? accelerate has more GitHub stars (9,803 vs 113). Stars measure visibility, not whether either tool fits your constraints. ### Are accelerate and octoml-profile open source? Yes - both are open-source projects on GitHub (accelerate: Apache-2.0, octoml-profile: Apache-2.0). ### Where can I find alternatives to accelerate or octoml-profile? GraphCanon lists graph-backed alternatives at [accelerate alternatives](/tools/huggingface-accelerate/alternatives) and [octoml-profile alternatives](/tools/octoml-octoml-profile/alternatives) ([accelerate markdown twin](/tools/huggingface-accelerate/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/huggingface-accelerate-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, accelerate or octoml-profile? accelerate: Very active. 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 accelerate and octoml-profile? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [accelerate trust report](/tools/huggingface-accelerate/trust); [octoml-profile trust report](/tools/octoml-octoml-profile/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=huggingface-accelerate`](/api/graphcanon/graph?tool=huggingface-accelerate) - 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/_