--- title: "determined vs llm-app" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/determined-ai-determined-vs-pathwaycom-llm-app" tools: ["determined-ai-determined", "pathwaycom-llm-app"] --- # determined vs llm-app *GraphCanon updated Sep 30, 2026* ## Verdict Pick determined if determined is an open-source machine learning platform that simplifies distributed training and hyperparameter tuning for PyTorch and TensorFlow applications; pick llm-app if llm-app offers cloud templates for RAG, AI pipelines, and enterprise search, supporting integration with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs. [determined](https://determined.ai) reports 3.2k GitHub stars, 375 forks, and 108 open issues, last pushed Mar 20, 2025. [llm-app](https://pathway.com/developers/templates/) has 59k stars, 1.5k forks, and 8 open issues, last pushed Jul 5, 2026. Figures are from public GitHub metadata via [determined's repository](https://github.com/determined-ai/determined) and [llm-app's repository](https://github.com/pathwaycom/llm-app). | | [determined](/tools/determined-ai-determined.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Tagline | An open-source machine learning platform for distributed training and resource management. | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data | | Stars | 3,241 | 58,920 | | Forks | 375 | 1,498 | | Open issues | 108 | 8 | | Language | Go | Jupyter Notebook | | Adopt for | Determined is an open-source machine learning platform that simplifies distributed training and hyperparameter tuning for PyTorch and TensorFlow applications. | llm-app offers cloud templates for RAG, AI pipelines, and enterprise search, supporting integration with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT License | | Categories | Evaluation & Observability, Model Training | Data & Retrieval, Evaluation & Observability, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [determined](/tools/determined-ai-determined.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Steady (60%) | | Days since push | 558d | 74d | | Open issues (now) | 108 | 8 | | Stars delta | +14 (30d) | -117 (30d) | | Full report | [trust report](/tools/determined-ai-determined/trust.md) | [trust report](/tools/pathwaycom-llm-app/trust.md) | ## Decision facts: determined - **Pricing:** freemium - The open-source version under Apache License is free to use. Additional enterprise features may incur costs, though specific pricing details are not provided here. - **Requirements:** Installation involves using 'pip' for the CLI and subsequent cluster deployment steps via `det deploy`. - **Adopt for:** Determined is an open-source machine learning platform that simplifies distributed training and hyperparameter tuning for PyTorch and TensorFlow applications. - **License detail:** Apache-2.0 ## Decision facts: llm-app - **Pricing:** freemium - The repository is open-source under the MIT License, but additional services or support might incur costs. - **Requirements:** Min 4 GB RAM; Requires Docker; Requires Docker for running the cloud templates.; Supports integration with a variety of data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs. - **Adopt for:** llm-app offers cloud templates for RAG, AI pipelines, and enterprise search, supporting integration with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs. - **License detail:** MIT License ## Choose when ### Choose determined if… - determined is primarily Go; llm-app is Jupyter Notebook. - License: determined is Apache-2.0, llm-app is MIT. - Pricing: The open-source version under Apache License is free to use. Additional enterprise features may incur costs, though specific pricing details are not provided here.. - Requirements: Installation involves using 'pip' for the CLI and subsequent cluster deployment steps via `det deploy`.. - Tags unique to determined: data-science, deep-learning, distributed training, hyperparameter-optimization. - You require a streamlined solution for distributed model training, particularly if you are working with PyTorch or TensorFlow frameworks. ### Choose llm-app if… - llm-app is primarily Jupyter Notebook; determined is Go. - License: llm-app is MIT, determined is Apache-2.0. - Pricing: The repository is open-source under the MIT License, but additional services or support might incur costs.. - Requirements: Min 4 GB RAM; Requires Docker; Requires Docker for running the cloud templates.; Supports integration with a variety of data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs.. - Tags unique to llm-app: chatbot, hugging-face, llm, llm-local. - Also covers Data & Retrieval, Inference & Serving. - When you need ready-to-run cloud templates for RAG, AI pipelines, and enterprise search that integrate seamlessly with data sources such as Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-ti ## When NOT to use determined - Seeking a platform that supports more machine learning frameworks beyond PyTorch and TensorFlow. - Your current stack does not include any of the supported infrastructures like Kubernetes or cloud services where Determined can be deployed. ## When NOT to use llm-app - Avoid using llm-app if your project does not require integration with specific data sources like Sharepoint or Google Drive, as the tool's strength lies in its broad data source support. - Do not use llm-app if you are looking for a tool that focuses solely on model training or inference without the need for cloud templates or enterprise search capabilities. ## Common questions ### What is the difference between determined and llm-app? determined: An open-source machine learning platform for distributed training and resource management.. llm-app: Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. See the comparison table for live GitHub stats and shared categories. ### When should I choose determined over llm-app? Choose determined over llm-app when determined is primarily Go; llm-app is Jupyter Notebook; License: determined is Apache-2.0, llm-app is MIT; Pricing: The open-source version under Apache License is free to use. Additional enterprise features may incur costs, though specific pricing details are not provided here.; Requirements: Installation involves using 'pip' for the CLI and subsequent cluster deployment steps via `det deploy`.; Tags unique to determined: data-science, deep-learning, distributed training, hyperparameter-optimization; You require a streamlined solution for distributed model training, particularly if you are working with PyTorch or TensorFlow frameworks. ### When should I choose llm-app over determined? Choose llm-app over determined when llm-app is primarily Jupyter Notebook; determined is Go; License: llm-app is MIT, determined is Apache-2.0; Pricing: The repository is open-source under the MIT License, but additional services or support might incur costs.; Requirements: Min 4 GB RAM; Requires Docker; Requires Docker for running the cloud templates.; Supports integration with a variety of data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-time data APIs.; Tags unique to llm-app: chatbot, hugging-face, llm, llm-local; Also covers Data & Retrieval, Inference & Serving; When you need ready-to-run cloud templates for RAG, AI pipelines, and enterprise search that integrate seamlessly with data sources such as Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and real-ti. ### When should I avoid determined? Seeking a platform that supports more machine learning frameworks beyond PyTorch and TensorFlow. Your current stack does not include any of the supported infrastructures like Kubernetes or cloud services where Determined can be deployed. ### When should I avoid llm-app? Avoid using llm-app if your project does not require integration with specific data sources like Sharepoint or Google Drive, as the tool's strength lies in its broad data source support. Do not use llm-app if you are looking for a tool that focuses solely on model training or inference without the need for cloud templates or enterprise search capabilities. ### Is determined or llm-app more popular on GitHub? llm-app has more GitHub stars (58,920 vs 3,241). Stars measure visibility, not whether either tool fits your constraints. ### Are determined and llm-app open source? Yes - both are open-source projects on GitHub (determined: Apache-2.0, llm-app: MIT). ### Where can I find alternatives to determined or llm-app? GraphCanon lists graph-backed alternatives at [determined alternatives](/tools/determined-ai-determined/alternatives) and [llm-app alternatives](/tools/pathwaycom-llm-app/alternatives) ([determined markdown twin](/tools/determined-ai-determined/alternatives.md), [llm-app markdown twin](/tools/pathwaycom-llm-app/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/determined-ai-determined-vs-pathwaycom-llm-app.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, determined or llm-app? determined: Dormant. llm-app: Steady. 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 determined and llm-app? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [determined trust report](/tools/determined-ai-determined/trust); [llm-app trust report](/tools/pathwaycom-llm-app/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=determined-ai-determined`](/api/graphcanon/graph?tool=determined-ai-determined) - 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/_