--- title: "octoml-profile vs oumi" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/octoml-octoml-profile-vs-oumi-ai-oumi" tools: ["octoml-octoml-profile", "oumi-ai-oumi"] --- # octoml-profile vs oumi *GraphCanon updated Aug 23, 2026* ## Verdict Pick octoml-profile if octoML PyTorch Profiler provides profiling and acceleration tools for PyTorch models with remote execution capabilities; pick oumi if oumi is a tool for fine-tuning, evaluating, and deploying open-source large language models (LLMs) such as Gemma 4, Qwen3.5, Qwen3.6, gpt-oss, DeepSeek-R1, among others. [octoml-profile](https://github.com/octoml/octoml-profile) reports 113 GitHub stars, 10 forks, and 0 open issues, last pushed Apr 24, 2023. [oumi](https://oumi.ai) has 9.4k stars, 784 forks, and 34 open issues, last pushed Aug 21, 2026. Figures are from public GitHub metadata via [octoml-profile's repository](https://github.com/octoml/octoml-profile) and [oumi's repository](https://github.com/oumi-ai/oumi). | | [octoml-profile](/tools/octoml-octoml-profile.md) | [oumi](/tools/oumi-ai-oumi.md) | | --- | --- | --- | | Tagline | Home for OctoML PyTorch Profiler | Easily fine-tune, evaluate and deploy open source LLMs/VLMs | | Stars | 113 | 9,376 | | Forks | 10 | 784 | | Open issues | 0 | 34 | | Language | - | Python | | Adopt for | OctoML PyTorch Profiler provides profiling and acceleration tools for PyTorch models with remote execution capabilities. | Oumi is a tool for fine-tuning, evaluating, and deploying open-source large language models (LLMs) such as Gemma 4, Qwen3.5, Qwen3.6, gpt-oss, DeepSeek-R1, among others. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Oumi is released under Apache-2.0 license, providing users with a permissive free software license that includes the terms of the MIT License while also addressing patent liability issues. | | Categories | Inference & Serving, Model Training | Evaluation & Observability, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [octoml-profile](/tools/octoml-octoml-profile.md) | [oumi](/tools/oumi-ai-oumi.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 1197d | 1d | | Open issues (now) | 0 | 34 | | Stars delta | Unknown | +17 (30d) | | Open issues delta | Unknown | +3 (30d) | | Full report | [trust report](/tools/octoml-octoml-profile/trust.md) | [trust report](/tools/oumi-ai-oumi/trust.md) | ## Decision facts: octoml-profile - **Adopt for:** OctoML PyTorch Profiler provides profiling and acceleration tools for PyTorch models with remote execution capabilities. ## Decision facts: oumi - **Requirements:** Requires Docker; Docker is used for standardized and portable environment deployments. - **Adopt for:** Oumi is a tool for fine-tuning, evaluating, and deploying open-source large language models (LLMs) such as Gemma 4, Qwen3.5, Qwen3.6, gpt-oss, DeepSeek-R1, among others. - **License detail:** Oumi is released under Apache-2.0 license, providing users with a permissive free software license that includes the terms of the MIT License while also addressing patent liability issues. ## Choose when ### 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). ### Choose oumi if… - Requirements: Requires Docker; Docker is used for standardized and portable environment deployments.. - Tags unique to oumi: dpo, evaluation, fine-tuning, llms. - Also covers Evaluation & Observability. - oumi ships Docker support for self-hosted deployment. - - You are working specifically with one of the supported open-source LLMs including Gemma 4 or Qwen variants. ## 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 ## When NOT to use oumi - - If your focus is on proprietary models rather than open-source ones, Oumi may not offer the necessary support or integrations. - - You require deployment flexibility beyond what Oumi provides for less commonly supported open-source LLMs outside its primary focus (e.g., Gemma 4, Qwen series). ## Common questions ### What is the difference between octoml-profile and oumi? octoml-profile: Home for OctoML PyTorch Profiler. oumi: Easily fine-tune, evaluate and deploy open source LLMs/VLMs. See the comparison table for live GitHub stats and shared categories. ### When should I choose octoml-profile over oumi? Choose octoml-profile over oumi 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 oumi over octoml-profile? Choose oumi over octoml-profile when Requirements: Requires Docker; Docker is used for standardized and portable environment deployments.; Tags unique to oumi: dpo, evaluation, fine-tuning, llms; Also covers Evaluation & Observability; oumi ships Docker support for self-hosted deployment; - You are working specifically with one of the supported open-source LLMs including Gemma 4 or Qwen variants. ### 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 oumi? - If your focus is on proprietary models rather than open-source ones, Oumi may not offer the necessary support or integrations. - You require deployment flexibility beyond what Oumi provides for less commonly supported open-source LLMs outside its primary focus (e.g., Gemma 4, Qwen series). ### Is octoml-profile or oumi more popular on GitHub? oumi has more GitHub stars (9,376 vs 113). Stars measure visibility, not whether either tool fits your constraints. ### Are octoml-profile and oumi open source? Yes - both are open-source projects on GitHub (octoml-profile: Apache-2.0, oumi: Apache-2.0). ### Where can I find alternatives to octoml-profile or oumi? GraphCanon lists graph-backed alternatives at [octoml-profile alternatives](/tools/octoml-octoml-profile/alternatives) and [oumi alternatives](/tools/oumi-ai-oumi/alternatives) ([octoml-profile markdown twin](/tools/octoml-octoml-profile/alternatives.md), [oumi markdown twin](/tools/oumi-ai-oumi/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/octoml-octoml-profile-vs-oumi-ai-oumi.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, octoml-profile or oumi? octoml-profile: Dormant. oumi: 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 octoml-profile and oumi? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [octoml-profile trust report](/tools/octoml-octoml-profile/trust); [oumi trust report](/tools/oumi-ai-oumi/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=octoml-octoml-profile`](/api/graphcanon/graph?tool=octoml-octoml-profile) - 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/_