--- title: "DeepSpeed vs start-llms" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/deepspeedai-deepspeed-vs-louisfb01-start-llms" tools: ["deepspeedai-deepspeed", "louisfb01-start-llms"] --- # DeepSpeed vs start-llms *GraphCanon updated Jul 12, 2026* ## Verdict Pick DeepSpeed if 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; pick start-llms if a comprehensive beginner-friendly guide oriented towards developing Large Language Model (LLM) skills through the latest methods and industry practices. [DeepSpeed](https://www.deepspeed.ai/) reports 43k GitHub stars, 4.9k forks, and 1.3k open issues, last pushed Jul 11, 2026. [start-llms](https://www.louisbouchard.ai/from-zero-to-hero-with-llms/) has 978 stars, 127 forks, and 2 open issues, last pushed Jan 23, 2026. Figures are from public GitHub metadata via [DeepSpeed's repository](https://github.com/deepspeedai/DeepSpeed) and [start-llms's repository](https://github.com/louisfb01/start-llms). | | [DeepSpeed](/tools/deepspeedai-deepspeed.md) | [start-llms](/tools/louisfb01-start-llms.md) | | --- | --- | --- | | Tagline | Deep learning optimization library for efficient distributed training and inference | A comprehensive guide for beginners to advance in LLM skills and stay current with industry developments. | | Stars | 42,685 | 978 | | Forks | 4,883 | 127 | | Open issues | 1,302 | 2 | | Language | 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. | A comprehensive beginner-friendly guide oriented towards developing Large Language Model (LLM) skills through the latest methods and industry practices. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Model Training, Inference & Serving | Model Training, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [DeepSpeed](/tools/deepspeedai-deepspeed.md) | [start-llms](/tools/louisfb01-start-llms.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 168d | | Open issues (now) | 1.3k | 2 | | Owner type | Organization | User | | Full report | [trust report](/tools/deepspeedai-deepspeed/trust.md) | [trust report](/tools/louisfb01-start-llms/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. ## Decision facts: start-llms - **Adopt for:** A comprehensive beginner-friendly guide oriented towards developing Large Language Model (LLM) skills through the latest methods and industry practices. ## Choose when ### Choose DeepSpeed if… - License: DeepSpeed is Apache-2.0, start-llms is MIT. - Tags unique to DeepSpeed: deep-learning, gpu, compression, machine-learning. - Also covers Inference & Serving. - - When training or inferring with PyTorch on large datasets or complex deep learning models (up to trillion parameters) ### Choose start-llms if… - License: start-llms is MIT, DeepSpeed is Apache-2.0. - Tags unique to start-llms: llama, fine-tuning, ai, large-language-models. - Also covers Evaluation & Observability. - You are a newcomer to LLMs looking for an accessible introductory pathway. ## 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 start-llms - You already have advanced expertise or are a seasoned professional who prefers to dive deep into specialized areas immediately. - Your primary objective is real-time collaboration features for model development teams, as the repository does not highlight these aspects. ## Common questions ### What is the difference between DeepSpeed and start-llms? DeepSpeed: Deep learning optimization library for efficient distributed training and inference. start-llms: A comprehensive guide for beginners to advance in LLM skills and stay current with industry developments.. See the comparison table for live GitHub stats and shared categories. ### When should I choose DeepSpeed over start-llms? Choose DeepSpeed over start-llms when License: DeepSpeed is Apache-2.0, start-llms is MIT; Tags unique to DeepSpeed: deep-learning, gpu, compression, machine-learning; Also covers Inference & Serving; - When training or inferring with PyTorch on large datasets or complex deep learning models (up to trillion parameters). ### When should I choose start-llms over DeepSpeed? Choose start-llms over DeepSpeed when License: start-llms is MIT, DeepSpeed is Apache-2.0; Tags unique to start-llms: llama, fine-tuning, ai, large-language-models; Also covers Evaluation & Observability; You are a newcomer to LLMs looking for an accessible introductory pathway. ### 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 start-llms? You already have advanced expertise or are a seasoned professional who prefers to dive deep into specialized areas immediately. Your primary objective is real-time collaboration features for model development teams, as the repository does not highlight these aspects. ### Is DeepSpeed or start-llms more popular on GitHub? DeepSpeed has more GitHub stars (42,685 vs 978). Stars measure visibility, not whether either tool fits your constraints. ### Are DeepSpeed and start-llms open source? Yes - both are open-source projects on GitHub (DeepSpeed: Apache-2.0, start-llms: MIT). ### Where can I find alternatives to DeepSpeed or start-llms? GraphCanon lists graph-backed alternatives at [DeepSpeed alternatives](/tools/deepspeedai-deepspeed/alternatives) and [start-llms alternatives](/tools/louisfb01-start-llms/alternatives) ([DeepSpeed markdown twin](/tools/deepspeedai-deepspeed/alternatives.md), [start-llms markdown twin](/tools/louisfb01-start-llms/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-louisfb01-start-llms.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, DeepSpeed or start-llms? DeepSpeed: Very active. start-llms: Slowing. 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 start-llms? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [DeepSpeed trust report](/tools/deepspeedai-deepspeed/trust); [start-llms trust report](/tools/louisfb01-start-llms/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/_