---
title: "awesome-free-llm-apis vs awesome-LLM-resources"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/mnfst-awesome-free-llm-apis-vs-wangrongsheng-awesome-llm-resources"
tools: ["mnfst-awesome-free-llm-apis", "wangrongsheng-awesome-llm-resources"]
---

# awesome-free-llm-apis vs awesome-LLM-resources

*GraphCanon updated Sep 20, 2026*

## Verdict

Pick awesome-free-llm-apis if awesome-free-llm-apis curates permanent free Large Language Model APIs with notable details on their limitations and access methods; pick awesome-LLM-resources if awesome-LLM-resources is a curated list of resources related to large language models, covering a wide range of topics from multimodal generation to model training and inference.

[awesome-free-llm-apis](https://github.com/mnfst/awesome-free-llm-apis) reports 7.9k GitHub stars, 746 forks, and 17 open issues, last pushed Aug 21, 2026. [awesome-LLM-resources](https://github.com/WangRongsheng/awesome-LLM-resources) has 9.0k stars, 993 forks, and 40 open issues, last pushed Sep 14, 2026. Figures are from public GitHub metadata via [awesome-free-llm-apis's repository](https://github.com/mnfst/awesome-free-llm-apis) and [awesome-LLM-resources's repository](https://github.com/WangRongsheng/awesome-LLM-resources).

| | [awesome-free-llm-apis](/tools/mnfst-awesome-free-llm-apis.md) | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) |
| --- | --- | --- |
| Tagline | List of Permanent Free LLM API | Summary of the world's best LLM resources. |
| Stars | 7,852 | 8,968 |
| Forks | 746 | 993 |
| Open issues | 17 | 40 |
| Language | JavaScript | - |
| Adopt for | awesome-free-llm-apis curates permanent free Large Language Model APIs with notable details on their limitations and access methods. | awesome-LLM-resources is a curated list of resources related to large language models, covering a wide range of topics from multimodal generation to model training and inference. |
| Persona | - | - |
| Runtime | - | - |
| License | This resource is distributed under the Creative Commons Zero v1.0 Universal Public Domain Dedication (CC0-1.0) license. | The repository is licensed under Apache-2.0, allowing for free use, modification, and distribution. |
| Categories | Inference & Serving | AI Agents, Computer Vision, Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training |

## Trust and health

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

| | [awesome-free-llm-apis](/tools/mnfst-awesome-free-llm-apis.md) | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) |
| --- | --- | --- |
| Maintenance | Active (82%) | Very active (96%) |
| Days since push | 29d | 3d |
| Open issues (now) | 17 | 40 |
| Stars delta | +1.3k (30d) | +123 (30d) |
| Open issues delta | -8 (30d) | +17 (30d) |
| Owner type | Organization | User |
| Full report | [trust report](/tools/mnfst-awesome-free-llm-apis/trust.md) | [trust report](/tools/wangrongsheng-awesome-llm-resources/trust.md) |

## Decision facts: awesome-free-llm-apis

- **Pricing:** freemium - The repository lists APIs with permanent free tiers, detailing rate and token limits for those interested in using free Large Language Model services.
- **Requirements:** Before integration, ensure that the specific requirements for API access are met to utilize these models without restriction.; Users should review the rate and token limits associated with each API provider to determine suitability based on their project's needs.
- **Adopt for:** awesome-free-llm-apis curates permanent free Large Language Model APIs with notable details on their limitations and access methods.
- **License detail:** This resource is distributed under the Creative Commons Zero v1.0 Universal Public Domain Dedication (CC0-1.0) license.

## Decision facts: awesome-LLM-resources

- **Pricing:** freemium - The repository itself is free to use, but some linked resources may require payment or have associated costs.
- **Requirements:** The repository does not specify any technical requirements for accessing its content.
- **Adopt for:** awesome-LLM-resources is a curated list of resources related to large language models, covering a wide range of topics from multimodal generation to model training and inference.
- **License detail:** The repository is licensed under Apache-2.0, allowing for free use, modification, and distribution.

## Choose when

### Choose awesome-free-llm-apis if…

- License: awesome-free-llm-apis is CC0-1.0, awesome-LLM-resources is Apache-2.0.
- Pricing: The repository lists APIs with permanent free tiers, detailing rate and token limits for those interested in using free Large Language Model services..
- Requirements: Before integration, ensure that the specific requirements for API access are met to utilize these models without restriction.; Users should review the rate and token limits associated with each API provider to determine suitability based on their project's needs..
- Tags unique to awesome-free-llm-apis: ai-agents, anthropic, gemini, ollama.
- When you need text inference with specialized capabilities like roleplay and storytelling, the Aion Labs API offers a dedicated free tier specifically designed for these purposes.

### Choose awesome-LLM-resources if…

- License: awesome-LLM-resources is Apache-2.0, awesome-free-llm-apis is CC0-1.0.
- Pricing: The repository itself is free to use, but some linked resources may require payment or have associated costs..
- Requirements: The repository does not specify any technical requirements for accessing its content..
- Tags unique to awesome-LLM-resources: awesome-list, book, course, large-language-models.
- Also covers AI Agents, Computer Vision, Data & Retrieval, Developer Tools, Evaluation & Observability, LLM Frameworks, Model Training.
- When you need a comprehensive list of resources for large language models, including multimodal generation, agents, programming assistance, and more.

## When NOT to use awesome-free-llm-apis

- Avoid using Aion Labs if your project involves heavy commercial activity, given its limited rate and token limits.
- Do not use Cohere for projects that will scale beyond 1,000 API calls per month or require credit card details for access to higher-tier plans.
- Google Gemini's free tier is inaccessible in the EU/UK/Switzerland regions and requires consent to let Google improve their products through your usage.
- Mistral AI should be avoided if you need strict confidentiality, as they use prompts from users' interactions to refine and train additional model iterations.

## When NOT to use awesome-LLM-resources

- If you are looking for a tool that provides direct access to LLM APIs or services, as this repository is a list of resources rather than a service provider.
- When you need real-time support or a community forum for troubleshooting LLM-related issues, as this repository is a static list of resources without interactive support.

## Common questions

### What is the difference between awesome-free-llm-apis and awesome-LLM-resources?

awesome-free-llm-apis: List of Permanent Free LLM API. awesome-LLM-resources: Summary of the world's best LLM resources.. See the comparison table for live GitHub stats and shared categories.

### When should I choose awesome-free-llm-apis over awesome-LLM-resources?

Choose awesome-free-llm-apis over awesome-LLM-resources when License: awesome-free-llm-apis is CC0-1.0, awesome-LLM-resources is Apache-2.0; Pricing: The repository lists APIs with permanent free tiers, detailing rate and token limits for those interested in using free Large Language Model services.; Requirements: Before integration, ensure that the specific requirements for API access are met to utilize these models without restriction.; Users should review the rate and token limits associated with each API provider to determine suitability based on their project's needs.; Tags unique to awesome-free-llm-apis: ai-agents, anthropic, gemini, ollama; When you need text inference with specialized capabilities like roleplay and storytelling, the Aion Labs API offers a dedicated free tier specifically designed for these purposes.

### When should I choose awesome-LLM-resources over awesome-free-llm-apis?

Choose awesome-LLM-resources over awesome-free-llm-apis when License: awesome-LLM-resources is Apache-2.0, awesome-free-llm-apis is CC0-1.0; Pricing: The repository itself is free to use, but some linked resources may require payment or have associated costs.; Requirements: The repository does not specify any technical requirements for accessing its content.; Tags unique to awesome-LLM-resources: awesome-list, book, course, large-language-models; Also covers AI Agents, Computer Vision, Data & Retrieval, Developer Tools, Evaluation & Observability, LLM Frameworks, Model Training; When you need a comprehensive list of resources for large language models, including multimodal generation, agents, programming assistance, and more.

### When should I avoid awesome-free-llm-apis?

Avoid using Aion Labs if your project involves heavy commercial activity, given its limited rate and token limits. Do not use Cohere for projects that will scale beyond 1,000 API calls per month or require credit card details for access to higher-tier plans. Google Gemini's free tier is inaccessible in the EU/UK/Switzerland regions and requires consent to let Google improve their products through your usage. Mistral AI should be avoided if you need strict confidentiality, as they use prompts from users' interactions to refine and train additional model iterations.

### When should I avoid awesome-LLM-resources?

If you are looking for a tool that provides direct access to LLM APIs or services, as this repository is a list of resources rather than a service provider. When you need real-time support or a community forum for troubleshooting LLM-related issues, as this repository is a static list of resources without interactive support.

### Is awesome-free-llm-apis or awesome-LLM-resources more popular on GitHub?

awesome-LLM-resources has more GitHub stars (8,968 vs 7,852). Stars measure visibility, not whether either tool fits your constraints.

### Are awesome-free-llm-apis and awesome-LLM-resources open source?

Yes - both are open-source projects on GitHub (awesome-free-llm-apis: CC0-1.0, awesome-LLM-resources: Apache-2.0).

### Where can I find alternatives to awesome-free-llm-apis or awesome-LLM-resources?

GraphCanon lists graph-backed alternatives at [awesome-free-llm-apis alternatives](/tools/mnfst-awesome-free-llm-apis/alternatives) and [awesome-LLM-resources alternatives](/tools/wangrongsheng-awesome-llm-resources/alternatives) ([awesome-free-llm-apis markdown twin](/tools/mnfst-awesome-free-llm-apis/alternatives.md), [awesome-LLM-resources markdown twin](/tools/wangrongsheng-awesome-llm-resources/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/mnfst-awesome-free-llm-apis-vs-wangrongsheng-awesome-llm-resources.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, awesome-free-llm-apis or awesome-LLM-resources?

awesome-free-llm-apis: Active. awesome-LLM-resources: Very 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 awesome-free-llm-apis and awesome-LLM-resources?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-free-llm-apis trust report](/tools/mnfst-awesome-free-llm-apis/trust); [awesome-LLM-resources trust report](/tools/wangrongsheng-awesome-llm-resources/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=mnfst-awesome-free-llm-apis`](/api/graphcanon/graph?tool=mnfst-awesome-free-llm-apis)
- 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/_