--- title: "DeepSpeed vs viewflow" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/deepspeedai-deepspeed-vs-viewflow-viewflow" tools: ["deepspeedai-deepspeed", "viewflow-viewflow"] --- # DeepSpeed vs viewflow *GraphCanon updated Jul 15, 2026* ## Verdict Pick DeepSpeed when license: DeepSpeed is Apache-2.0, viewflow is AGPL-3.0; pick viewflow when license: viewflow is AGPL-3.0, DeepSpeed is Apache-2.0. [DeepSpeed](https://www.deepspeed.ai/) reports 43k GitHub stars, 4.9k forks, and 1.3k open issues, last pushed Jul 13, 2026. [viewflow](http://viewflow.io) has 2.9k stars, 412 forks, and 9 open issues, last pushed Jul 6, 2026. Figures are from public GitHub metadata via [DeepSpeed's repository](https://github.com/deepspeedai/DeepSpeed) and [viewflow's repository](https://github.com/viewflow/viewflow). | | [DeepSpeed](/tools/deepspeedai-deepspeed.md) | [viewflow](/tools/viewflow-viewflow.md) | | --- | --- | --- | | Tagline | Deep learning optimization library for efficient distributed training and inference | Reusable workflow library for Django | | Stars | 42,700 | 2,865 | | Forks | 4,881 | 412 | | Open issues | 1,299 | 9 | | Language | Python | Python | | Adopt for | Decisions for DeepSpeed use are driven by its capacity to handle large models efficiently using techniques such as data parallelism, model parallelism, pipeline parallelism, and compression. | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | AGPL-3.0 | | Categories | Inference & Serving, Model Training | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [DeepSpeed](/tools/deepspeedai-deepspeed.md) | [viewflow](/tools/viewflow-viewflow.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 9d | | Open issues (now) | 1.3k | 9 | | Full report | [trust report](/tools/deepspeedai-deepspeed/trust.md) | [trust report](/tools/viewflow-viewflow/trust.md) | ## Decision facts: DeepSpeed - **Adopt for:** Decisions for DeepSpeed use are driven by its capacity to handle large models efficiently using techniques such as data parallelism, model parallelism, pipeline parallelism, and compression. ## Choose when ### Choose DeepSpeed if… - License: DeepSpeed is Apache-2.0, viewflow is AGPL-3.0. - Tags unique to DeepSpeed: billion-parameters, compression, data-parallelism, deep-learning. - Also covers Model Training. - - When training or inferring with PyTorch on large datasets or complex deep learning models (up to trillion parameters) ### Choose viewflow if… - License: viewflow is AGPL-3.0, DeepSpeed is Apache-2.0. - Tags unique to viewflow: bpmn, django, process-engine, python. - Leaner open-issue backlog (9). ## When NOT to use DeepSpeed - - When you are working in an environment that only supports CPU-based training without access to CUDA or ROCm compatible GPUs - - If your project's PyTorch version is less than 2.0, DeepSpeed may not support all of its features and optimizations effectively ## When NOT to use viewflow - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## Common questions ### What is the difference between DeepSpeed and viewflow? DeepSpeed: Deep learning optimization library for efficient distributed training and inference. viewflow: Reusable workflow library for Django. See the comparison table for live GitHub stats and shared categories. ### When should I choose DeepSpeed over viewflow? Choose DeepSpeed over viewflow when License: DeepSpeed is Apache-2.0, viewflow is AGPL-3.0; Tags unique to DeepSpeed: billion-parameters, compression, data-parallelism, deep-learning; Also covers Model Training; - When training or inferring with PyTorch on large datasets or complex deep learning models (up to trillion parameters). ### When should I choose viewflow over DeepSpeed? Choose viewflow over DeepSpeed when License: viewflow is AGPL-3.0, DeepSpeed is Apache-2.0; Tags unique to viewflow: bpmn, django, process-engine, python; Leaner open-issue backlog (9). ### When should I avoid DeepSpeed? - When you are working in an environment that only supports CPU-based training without access to CUDA or ROCm compatible GPUs - If your project's PyTorch version is less than 2.0, DeepSpeed may not support all of its features and optimizations effectively ### When should I avoid viewflow? Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### Is DeepSpeed or viewflow more popular on GitHub? DeepSpeed has more GitHub stars (42,700 vs 2,865). Stars measure visibility, not whether either tool fits your constraints. ### Are DeepSpeed and viewflow open source? Yes - both are open-source projects on GitHub (DeepSpeed: Apache-2.0, viewflow: AGPL-3.0). ### Where can I find alternatives to DeepSpeed or viewflow? GraphCanon lists graph-backed alternatives at [DeepSpeed alternatives](/tools/deepspeedai-deepspeed/alternatives) and [viewflow alternatives](/tools/viewflow-viewflow/alternatives) ([DeepSpeed markdown twin](/tools/deepspeedai-deepspeed/alternatives.md), [viewflow markdown twin](/tools/viewflow-viewflow/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/deepspeedai-deepspeed-vs-viewflow-viewflow.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, DeepSpeed or viewflow? DeepSpeed: Very active. viewflow: 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 DeepSpeed and viewflow? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [DeepSpeed trust report](/tools/deepspeedai-deepspeed/trust); [viewflow trust report](/tools/viewflow-viewflow/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=deepspeedai-deepspeed`](/api/graphcanon/graph?tool=deepspeedai-deepspeed) - 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/_