--- title: "llm-engineer-toolkit vs ray-llm" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/kalyanks-nlp-llm-engineer-toolkit-vs-ray-project-ray-llm" tools: ["kalyanks-nlp-llm-engineer-toolkit", "ray-project-ray-llm"] --- # llm-engineer-toolkit vs ray-llm *GraphCanon updated Sep 20, 2026* ## Verdict Pick llm-engineer-toolkit if the llm-engineer-toolkit is a curated list of over 120 LLM libraries, organized into categories such as LLM Training, Inference, and Serving, aimed at LLM engineers and developers; pick ray-llm if ray-LLM is an archived project for deploying large language models on Ray, with its functionalities now integrated into the Ray framework through the ray.serve.llm and ray.data.llm APIs. [llm-engineer-toolkit](https://www.linkedin.com/in/kalyanksnlp/) reports 11k GitHub stars, 1.7k forks, and 17 open issues, last pushed Sep 9, 2026. [ray-llm](https://docs.ray.io/en/latest/) has 1.3k stars, 90 forks, and 0 open issues, last pushed Mar 13, 2025. Figures are from public GitHub metadata via [llm-engineer-toolkit's repository](https://github.com/KalyanKS-NLP/llm-engineer-toolkit) and [ray-llm's repository](https://github.com/ray-project/ray-llm). | | [llm-engineer-toolkit](/tools/kalyanks-nlp-llm-engineer-toolkit.md) | [ray-llm](/tools/ray-project-ray-llm.md) | | --- | --- | --- | | Tagline | A curated list of 120+ LLM libraries category wise | Archived repository for LLMs on Ray, now integrated into Ray. | | Stars | 10,793 | 1,261 | | Forks | 1,687 | 90 | | Open issues | 17 | 0 | | Language | - | - | | Adopt for | The llm-engineer-toolkit is a curated list of over 120 LLM libraries, organized into categories such as LLM Training, Inference, and Serving, aimed at LLM engineers and developers. | Ray-LLM is an archived project for deploying large language models on Ray, with its functionalities now integrated into the Ray framework through the ray.serve.llm and ray.data.llm APIs. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | License information is not provided. | | Categories | Inference & Serving, LLM Frameworks, Model Training | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [llm-engineer-toolkit](/tools/kalyanks-nlp-llm-engineer-toolkit.md) | [ray-llm](/tools/ray-project-ray-llm.md) | | --- | --- | --- | | Maintenance | Active (82%) | Archived (8%) | | Days since push | 9d | 554d | | Archived on GitHub | No | Yes | | Open issues (now) | 17 | 0 | | Stars delta | +26 (30d) | 0 (30d) | | Open issues delta | +2 (30d) | 0 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/kalyanks-nlp-llm-engineer-toolkit/trust.md) | [trust report](/tools/ray-project-ray-llm/trust.md) | ## Decision facts: llm-engineer-toolkit - **Adopt for:** The llm-engineer-toolkit is a curated list of over 120 LLM libraries, organized into categories such as LLM Training, Inference, and Serving, aimed at LLM engineers and developers. ## Decision facts: ray-llm - **Pricing:** unknown - Pricing details are not available. - **Requirements:** Ensure you have the latest version of Ray installed to use the ray.serve.llm and ray.data.llm APIs. - **Adopt for:** Ray-LLM is an archived project for deploying large language models on Ray, with its functionalities now integrated into the Ray framework through the ray.serve.llm and ray.data.llm APIs. - **License detail:** License information is not provided. ## Choose when ### Choose llm-engineer-toolkit if… - Tags unique to llm-engineer-toolkit: ai-engineer, generative-ai, large-language-models, llm-engineer. - Also covers LLM Frameworks. - When you need a categorized list of over 120 LLM libraries to streamline your search for specific tools or frameworks. ### Choose ray-llm if… - Pricing: Pricing details are not available.. - Requirements: Ensure you have the latest version of Ray installed to use the ray.serve.llm and ray.data.llm APIs.. - Tags unique to ray-llm: llm, llm-serving, ray. - If you are working with Ray and need to deploy large language models, use the ray.serve.llm and ray.data.llm APIs, which are now integrated into the Ray framework. ## When NOT to use llm-engineer-toolkit - If you are seeking a repository that provides detailed implementation guides or code samples for each library, as the llm-engineer-toolkit primarily serves as a list. - When you require real-time updates or active development support, as the toolkit is a static list and does not include active development or community support features. ## When NOT to use ray-llm - Do not use the archived Ray-LLM repository for active development or deployment, as it is no longer maintained and its functionalities have been integrated into the Ray framework. - If you require the latest features and support for deploying large language models, avoid the archived repository and use the ray.serve.llm and ray.data.llm APIs directly. ## Common questions ### What is the difference between llm-engineer-toolkit and ray-llm? llm-engineer-toolkit: A curated list of 120+ LLM libraries category wise. ray-llm: Archived repository for LLMs on Ray, now integrated into Ray.. See the comparison table for live GitHub stats and shared categories. ### When should I choose llm-engineer-toolkit over ray-llm? Choose llm-engineer-toolkit over ray-llm when Tags unique to llm-engineer-toolkit: ai-engineer, generative-ai, large-language-models, llm-engineer; Also covers LLM Frameworks; When you need a categorized list of over 120 LLM libraries to streamline your search for specific tools or frameworks. ### When should I choose ray-llm over llm-engineer-toolkit? Choose ray-llm over llm-engineer-toolkit when Pricing: Pricing details are not available.; Requirements: Ensure you have the latest version of Ray installed to use the ray.serve.llm and ray.data.llm APIs.; Tags unique to ray-llm: llm, llm-serving, ray; If you are working with Ray and need to deploy large language models, use the ray.serve.llm and ray.data.llm APIs, which are now integrated into the Ray framework. ### When should I avoid llm-engineer-toolkit? If you are seeking a repository that provides detailed implementation guides or code samples for each library, as the llm-engineer-toolkit primarily serves as a list. When you require real-time updates or active development support, as the toolkit is a static list and does not include active development or community support features. ### When should I avoid ray-llm? Do not use the archived Ray-LLM repository for active development or deployment, as it is no longer maintained and its functionalities have been integrated into the Ray framework. If you require the latest features and support for deploying large language models, avoid the archived repository and use the ray.serve.llm and ray.data.llm APIs directly. ### Is llm-engineer-toolkit or ray-llm more popular on GitHub? llm-engineer-toolkit has more GitHub stars (10,793 vs 1,261). Stars measure visibility, not whether either tool fits your constraints. ### Are llm-engineer-toolkit and ray-llm open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to llm-engineer-toolkit or ray-llm? GraphCanon lists graph-backed alternatives at [llm-engineer-toolkit alternatives](/tools/kalyanks-nlp-llm-engineer-toolkit/alternatives) and [ray-llm alternatives](/tools/ray-project-ray-llm/alternatives) ([llm-engineer-toolkit markdown twin](/tools/kalyanks-nlp-llm-engineer-toolkit/alternatives.md), [ray-llm markdown twin](/tools/ray-project-ray-llm/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/kalyanks-nlp-llm-engineer-toolkit-vs-ray-project-ray-llm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, llm-engineer-toolkit or ray-llm? llm-engineer-toolkit: Active. ray-llm: Archived. 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 llm-engineer-toolkit and ray-llm? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [llm-engineer-toolkit trust report](/tools/kalyanks-nlp-llm-engineer-toolkit/trust); [ray-llm trust report](/tools/ray-project-ray-llm/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=kalyanks-nlp-llm-engineer-toolkit`](/api/graphcanon/graph?tool=kalyanks-nlp-llm-engineer-toolkit) - 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/_