---
title: "open-llms vs awesome-generative-ai"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/eugeneyan-open-llms-vs-filipecalegario-awesome-generative-ai"
tools: ["eugeneyan-open-llms", "filipecalegario-awesome-generative-ai"]
---

# open-llms vs awesome-generative-ai

*GraphCanon updated Sep 20, 2026*

## Verdict

Pick open-llms if open-llms is a curated list of open-source large language models (LLMs) that are licensed for commercial use, providing details such as release date, parameters, context length, and licensing terms; pick awesome-generative-ai if awesome-generative-ai offers an extensive directory of resources on generative AI spanning from models to artwork without coding or setup.

[open-llms](https://github.com/eugeneyan/open-llms) reports 13k GitHub stars, 988 forks, and 10 open issues, last pushed Feb 13, 2025. [awesome-generative-ai](https://github.com/filipecalegario/awesome-generative-ai) has 3.5k stars, 885 forks, and 317 open issues, last pushed Dec 18, 2025. Figures are from public GitHub metadata via [open-llms's repository](https://github.com/eugeneyan/open-llms) and [awesome-generative-ai's repository](https://github.com/filipecalegario/awesome-generative-ai).

| | [open-llms](/tools/eugeneyan-open-llms.md) | [awesome-generative-ai](/tools/filipecalegario-awesome-generative-ai.md) |
| --- | --- | --- |
| Tagline | A list of open LLMs available for commercial use | A comprehensive list of generative AI resources |
| Stars | 12,876 | 3,539 |
| Forks | 988 | 885 |
| Open issues | 10 | 317 |
| Language | - | - |
| Adopt for | open-llms is a curated list of open-source large language models (LLMs) that are licensed for commercial use, providing details such as release date, parameters, context length, and licensing terms. | awesome-generative-ai offers an extensive directory of resources on generative AI spanning from models to artwork without coding or setup. |
| Persona | - | - |
| Runtime | - | - |
| License | The repository itself is licensed under Apache-2.0, but the models listed have various licenses, including Apache 2.0, MIT, and OpenRAIL-M. | CC0-1.0 - public domain with no attribution required, ideal for broad distribution and integration in any project without legal constraints. |
| Categories | LLM Frameworks | AI Agents, Computer Vision, Data & Retrieval, Developer Tools, LLM Frameworks, Speech & Audio |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [open-llms](/tools/eugeneyan-open-llms.md) | [awesome-generative-ai](/tools/filipecalegario-awesome-generative-ai.md) |
| --- | --- | --- |
| Maintenance | Dormant (18%) | Slowing (36%) |
| Days since push | 582d | 275d |
| Open issues (now) | 10 | 317 |
| Stars delta | +27 (30d) | +31 (30d) |
| Open issues delta | -1 (30d) | +56 (30d) |
| Full report | [trust report](/tools/eugeneyan-open-llms/trust.md) | [trust report](/tools/filipecalegario-awesome-generative-ai/trust.md) |

## Decision facts: open-llms

- **Pricing:** freemium - The repository is free to use, but the commercial use of the models listed may require adherence to their respective licensing terms.
- **Requirements:** Min 8 GB RAM; The specific requirements for running the models listed in the repository vary and should be checked individually.
- **Adopt for:** open-llms is a curated list of open-source large language models (LLMs) that are licensed for commercial use, providing details such as release date, parameters, context length, and licensing terms.
- **License detail:** The repository itself is licensed under Apache-2.0, but the models listed have various licenses, including Apache 2.0, MIT, and OpenRAIL-M.

## Decision facts: awesome-generative-ai

- **Adopt for:** awesome-generative-ai offers an extensive directory of resources on generative AI spanning from models to artwork without coding or setup.
- **License detail:** CC0-1.0 - public domain with no attribution required, ideal for broad distribution and integration in any project without legal constraints.

## Choose when

### Choose open-llms if…

- License: open-llms is Apache-2.0, awesome-generative-ai is CC0-1.0.
- Pricing: The repository is free to use, but the commercial use of the models listed may require adherence to their respective licensing terms..
- Requirements: Min 8 GB RAM; The specific requirements for running the models listed in the repository vary and should be checked individually..
- Tags unique to open-llms: commercial, large-language-models, llm, llms.
- When you need a comprehensive list of open-source LLMs that are licensed for commercial use, including details like release date, parameters, and context length.

### Choose awesome-generative-ai if…

- License: awesome-generative-ai is CC0-1.0, open-llms is Apache-2.0.
- Tags unique to awesome-generative-ai: ai art, awesome-list, chatgpt, dall-e.
- Also covers AI Agents, Computer Vision, Data & Retrieval, Developer Tools, Speech & Audio.
- You want a curated list covering a broad range of generative AI tools and models.

## When NOT to use open-llms

- If you need models that are not open-source or are not licensed for commercial use, as open-llms exclusively lists models that are both open-source and commercially usable.
- When you require real-time updates or the latest models not yet included in the repository, as the list may not be updated as frequently as other sources.
- If you are looking for models with specific features not covered in the repository, such as fine-tuned models for particular tasks, as the repository focuses on general model information.

## When NOT to use awesome-generative-ai

- Seeking direct tool functionality or hands-on code implementation support.
- Looking for resources focused on specific frameworks like TensorFlow or PyTorch exclusively.

## Common questions

### What is the difference between open-llms and awesome-generative-ai?

open-llms: A list of open LLMs available for commercial use. awesome-generative-ai: A comprehensive list of generative AI resources. See the comparison table for live GitHub stats and shared categories.

### When should I choose open-llms over awesome-generative-ai?

Choose open-llms over awesome-generative-ai when License: open-llms is Apache-2.0, awesome-generative-ai is CC0-1.0; Pricing: The repository is free to use, but the commercial use of the models listed may require adherence to their respective licensing terms.; Requirements: Min 8 GB RAM; The specific requirements for running the models listed in the repository vary and should be checked individually.; Tags unique to open-llms: commercial, large-language-models, llm, llms; When you need a comprehensive list of open-source LLMs that are licensed for commercial use, including details like release date, parameters, and context length.

### When should I choose awesome-generative-ai over open-llms?

Choose awesome-generative-ai over open-llms when License: awesome-generative-ai is CC0-1.0, open-llms is Apache-2.0; Tags unique to awesome-generative-ai: ai art, awesome-list, chatgpt, dall-e; Also covers AI Agents, Computer Vision, Data & Retrieval, Developer Tools, Speech & Audio; You want a curated list covering a broad range of generative AI tools and models.

### When should I avoid open-llms?

If you need models that are not open-source or are not licensed for commercial use, as open-llms exclusively lists models that are both open-source and commercially usable. When you require real-time updates or the latest models not yet included in the repository, as the list may not be updated as frequently as other sources. If you are looking for models with specific features not covered in the repository, such as fine-tuned models for particular tasks, as the repository focuses on general model information.

### When should I avoid awesome-generative-ai?

Seeking direct tool functionality or hands-on code implementation support. Looking for resources focused on specific frameworks like TensorFlow or PyTorch exclusively.

### Is open-llms or awesome-generative-ai more popular on GitHub?

open-llms has more GitHub stars (12,876 vs 3,539). Stars measure visibility, not whether either tool fits your constraints.

### Are open-llms and awesome-generative-ai open source?

Yes - both are open-source projects on GitHub (open-llms: Apache-2.0, awesome-generative-ai: CC0-1.0).

### Where can I find alternatives to open-llms or awesome-generative-ai?

GraphCanon lists graph-backed alternatives at [open-llms alternatives](/tools/eugeneyan-open-llms/alternatives) and [awesome-generative-ai alternatives](/tools/filipecalegario-awesome-generative-ai/alternatives) ([open-llms markdown twin](/tools/eugeneyan-open-llms/alternatives.md), [awesome-generative-ai markdown twin](/tools/filipecalegario-awesome-generative-ai/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/eugeneyan-open-llms-vs-filipecalegario-awesome-generative-ai.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, open-llms or awesome-generative-ai?

open-llms: Dormant. awesome-generative-ai: 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 open-llms and awesome-generative-ai?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [open-llms trust report](/tools/eugeneyan-open-llms/trust); [awesome-generative-ai trust report](/tools/filipecalegario-awesome-generative-ai/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=eugeneyan-open-llms`](/api/graphcanon/graph?tool=eugeneyan-open-llms)
- 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/_