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

# awesome-free-llm-apis vs inference

*GraphCanon updated Aug 14, 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 inference if unified production-ready inference API that supports a wide range of models and deployment methods.

[awesome-free-llm-apis](https://github.com/mnfst/awesome-free-llm-apis) reports 6.5k GitHub stars, 630 forks, and 25 open issues, last pushed Jul 30, 2026. [inference](https://inference.readthedocs.io) has 9.5k stars, 851 forks, and 42 open issues, last pushed Aug 2, 2026. Figures are from public GitHub metadata via [awesome-free-llm-apis's repository](https://github.com/mnfst/awesome-free-llm-apis) and [inference's repository](https://github.com/xorbitsai/inference).

| | [awesome-free-llm-apis](/tools/mnfst-awesome-free-llm-apis.md) | [inference](/tools/xorbitsai-inference.md) |
| --- | --- | --- |
| Tagline | List of Permanent Free LLM API | Unified production-ready inference API for various models |
| Stars | 6,532 | 9,470 |
| Forks | 630 | 851 |
| Open issues | 25 | 42 |
| Language | JavaScript | Python |
| Adopt for | awesome-free-llm-apis curates permanent free Large Language Model APIs with notable details on their limitations and access methods. | Unified production-ready inference API that supports a wide range of models and deployment methods. |
| Persona | - | - |
| Runtime | - | - |
| License | This resource is distributed under the Creative Commons Zero v1.0 Universal Public Domain Dedication (CC0-1.0) license. | Apache-2.0 |
| Categories | Inference & Serving | Inference & Serving |

## Trust and health

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

| | [awesome-free-llm-apis](/tools/mnfst-awesome-free-llm-apis.md) | [inference](/tools/xorbitsai-inference.md) |
| --- | --- | --- |
| Maintenance | Active (82%) | Very active (96%) |
| Days since push | 14d | 0d |
| Open issues (now) | 25 | 42 |
| Full report | [trust report](/tools/mnfst-awesome-free-llm-apis/trust.md) | [trust report](/tools/xorbitsai-inference/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: inference

- **Pricing:** freemium - Primary core services offer under free Apache-2.0 license; advanced support might incur costs based on the deployment scale and environment complexity.
- **Requirements:** Min 4 GB RAM; Requires Docker; Compatibility with Nvidia GPUs requires Docker, CUDA setup.
- **Adopt for:** Unified production-ready inference API that supports a wide range of models and deployment methods.

## Choose when

### Choose awesome-free-llm-apis if…

- awesome-free-llm-apis is primarily JavaScript; inference is Python.
- License: awesome-free-llm-apis is CC0-1.0, inference 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, llm.
- 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 inference if…

- inference is primarily Python; awesome-free-llm-apis is JavaScript.
- License: inference is Apache-2.0, awesome-free-llm-apis is CC0-1.0.
- Pricing: Primary core services offer under free Apache-2.0 license; advanced support might incur costs based on the deployment scale and environment complexity..
- Requirements: Min 4 GB RAM; Requires Docker; Compatibility with Nvidia GPUs requires Docker, CUDA setup..
- Tags unique to inference: artificial-intelligence, deployment, machine-learning.
- - When you need to deploy multiple types of models (like speech, text, and multimodal) through a single unified interface.

## 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 inference

- - When strict control over individual model interfaces is required and a unified API complicates your workflow.
- - If you’re working with proprietary models that aren’t supported by Xinference’s built-in or custom integration mechanisms.
- - In cases where the project mandates use of specific deployment tools that are not well-aligned with Xinference’s recommended methods (e.g., Docker, Kubernetes), unless you can adapt your setup.

## Common questions

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

awesome-free-llm-apis: List of Permanent Free LLM API. inference: Unified production-ready inference API for various models. See the comparison table for live GitHub stats and shared categories.

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

Choose awesome-free-llm-apis over inference when awesome-free-llm-apis is primarily JavaScript; inference is Python; License: awesome-free-llm-apis is CC0-1.0, inference 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, llm; 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 inference over awesome-free-llm-apis?

Choose inference over awesome-free-llm-apis when inference is primarily Python; awesome-free-llm-apis is JavaScript; License: inference is Apache-2.0, awesome-free-llm-apis is CC0-1.0; Pricing: Primary core services offer under free Apache-2.0 license; advanced support might incur costs based on the deployment scale and environment complexity.; Requirements: Min 4 GB RAM; Requires Docker; Compatibility with Nvidia GPUs requires Docker, CUDA setup.; Tags unique to inference: artificial-intelligence, deployment, machine-learning; - When you need to deploy multiple types of models (like speech, text, and multimodal) through a single unified interface.

### 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 inference?

- When strict control over individual model interfaces is required and a unified API complicates your workflow. - If you’re working with proprietary models that aren’t supported by Xinference’s built-in or custom integration mechanisms. - In cases where the project mandates use of specific deployment tools that are not well-aligned with Xinference’s recommended methods (e.g., Docker, Kubernetes), unless you can adapt your setup.

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

inference has more GitHub stars (9,470 vs 6,532). Stars measure visibility, not whether either tool fits your constraints.

### Are awesome-free-llm-apis and inference open source?

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

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

GraphCanon lists graph-backed alternatives at [awesome-free-llm-apis alternatives](/tools/mnfst-awesome-free-llm-apis/alternatives) and [inference alternatives](/tools/xorbitsai-inference/alternatives) ([awesome-free-llm-apis markdown twin](/tools/mnfst-awesome-free-llm-apis/alternatives.md), [inference markdown twin](/tools/xorbitsai-inference/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-xorbitsai-inference.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 inference?

awesome-free-llm-apis: Active. inference: 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 inference?

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); [inference trust report](/tools/xorbitsai-inference/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/_