---
title: "Made-With-ML vs maclocal-api"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/gokumohandas-made-with-ml-vs-scouzi1966-maclocal-api"
tools: ["gokumohandas-made-with-ml", "scouzi1966-maclocal-api"]
---

# Made-With-ML vs maclocal-api

*GraphCanon updated Jul 15, 2026*

## Verdict

Pick Made-With-ML when made-With-ML is primarily Jupyter Notebook; maclocal-api is Swift; pick maclocal-api when maclocal-api is primarily Swift; Made-With-ML is Jupyter Notebook.

[Made-With-ML](https://madewithml.com) reports 49k GitHub stars, 7.7k forks, and 27 open issues, last pushed Mar 4, 2026. [maclocal-api](https://github.com/scouzi1966/maclocal-api) has 315 stars, 17 forks, and 23 open issues, last pushed Jul 14, 2026. Figures are from public GitHub metadata via [Made-With-ML's repository](https://github.com/GokuMohandas/Made-With-ML) and [maclocal-api's repository](https://github.com/scouzi1966/maclocal-api).

| | [Made-With-ML](/tools/gokumohandas-made-with-ml.md) | [maclocal-api](/tools/scouzi1966-maclocal-api.md) |
| --- | --- | --- |
| Tagline | Learn how to develop, deploy and iterate on production-grade ML applications. | 'afm' command cli: macOS server and single prompt mode that exposes Apple's Foundation and MLX Models and other APIs running on your Mac through a single aggregated OpenAI-compatible API endpoint. Sup |
| Stars | 48,703 | 315 |
| Forks | 7,661 | 17 |
| Open issues | 27 | 23 |
| Language | Jupyter Notebook | Swift |
| Adopt for | - | - |
| Persona | - | - |
| Runtime | - | - |
| License | MIT | MIT |
| Categories | AI Agents, LLM Frameworks, Model Training | Inference & Serving, LLM Frameworks, Model Training |

## Trust and health

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

| | [Made-With-ML](/tools/gokumohandas-made-with-ml.md) | [maclocal-api](/tools/scouzi1966-maclocal-api.md) |
| --- | --- | --- |
| Maintenance | Slowing (36%) | Very active (96%) |
| Days since push | 132d | 0d |
| Open issues (now) | 27 | 23 |
| Full report | [trust report](/tools/gokumohandas-made-with-ml/trust.md) | [trust report](/tools/scouzi1966-maclocal-api/trust.md) |

## Choose when

### Choose Made-With-ML if…

- Made-With-ML is primarily Jupyter Notebook; maclocal-api is Swift.
- Tags unique to Made-With-ML: data-engineering, data-quality, data-science, deep-learning.
- Also covers AI Agents.

### Choose maclocal-api if…

- maclocal-api is primarily Swift; Made-With-ML is Jupyter Notebook.
- Tags unique to maclocal-api: ai, apple-foundation-models, apple-intelligence, apple-llm.
- Also covers Inference & Serving.

## When NOT to use Made-With-ML

- Last GitHub push was 132 days ago (slowing maintenance, Mar 4, 2026). Validate activity before betting a new project on Made-With-ML.
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

## When NOT to use maclocal-api

- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

## Common questions

### What is the difference between Made-With-ML and maclocal-api?

Made-With-ML: Learn how to develop, deploy and iterate on production-grade ML applications.. maclocal-api: 'afm' command cli: macOS server and single prompt mode that exposes Apple's Foundation and MLX Models and other APIs running on your Mac through a single aggregated OpenAI-compatible API endpoint. Sup. See the comparison table for live GitHub stats and shared categories.

### When should I choose Made-With-ML over maclocal-api?

Choose Made-With-ML over maclocal-api when Made-With-ML is primarily Jupyter Notebook; maclocal-api is Swift; Tags unique to Made-With-ML: data-engineering, data-quality, data-science, deep-learning; Also covers AI Agents.

### When should I choose maclocal-api over Made-With-ML?

Choose maclocal-api over Made-With-ML when maclocal-api is primarily Swift; Made-With-ML is Jupyter Notebook; Tags unique to maclocal-api: ai, apple-foundation-models, apple-intelligence, apple-llm; Also covers Inference & Serving.

### When should I avoid Made-With-ML?

Last GitHub push was 132 days ago (slowing maintenance, Mar 4, 2026). Validate activity before betting a new project on Made-With-ML. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

### When should I avoid maclocal-api?

Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

### Is Made-With-ML or maclocal-api more popular on GitHub?

Made-With-ML has more GitHub stars (48,703 vs 315). Stars measure visibility, not whether either tool fits your constraints.

### Are Made-With-ML and maclocal-api open source?

Yes - both are open-source projects on GitHub (Made-With-ML: MIT, maclocal-api: MIT).

### Where can I find alternatives to Made-With-ML or maclocal-api?

GraphCanon lists graph-backed alternatives at [Made-With-ML alternatives](/tools/gokumohandas-made-with-ml/alternatives) and [maclocal-api alternatives](/tools/scouzi1966-maclocal-api/alternatives) ([Made-With-ML markdown twin](/tools/gokumohandas-made-with-ml/alternatives.md), [maclocal-api markdown twin](/tools/scouzi1966-maclocal-api/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/gokumohandas-made-with-ml-vs-scouzi1966-maclocal-api.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, Made-With-ML or maclocal-api?

Made-With-ML: Slowing. maclocal-api: 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 Made-With-ML and maclocal-api?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Made-With-ML trust report](/tools/gokumohandas-made-with-ml/trust); [maclocal-api trust report](/tools/scouzi1966-maclocal-api/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=gokumohandas-made-with-ml`](/api/graphcanon/graph?tool=gokumohandas-made-with-ml)
- 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/_