---
title: "Amphion vs manifold"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/open-mmlab-amphion-vs-uber-manifold"
tools: ["open-mmlab-amphion", "uber-manifold"]
---

# Amphion vs manifold

*GraphCanon updated Jul 11, 2026*

## Verdict

Pick Amphion when amphion is primarily Python; manifold is JavaScript; pick manifold when manifold is primarily JavaScript; Amphion is Python.

[Amphion](https://openhlt.github.io/amphion/) reports 9.9k GitHub stars, 822 forks, and 175 open issues, last pushed Mar 25, 2026. [manifold](https://github.com/uber/manifold) has 1.7k stars, 115 forks, and 83 open issues, last pushed Feb 5, 2025. Figures are from public GitHub metadata via [Amphion's repository](https://github.com/open-mmlab/Amphion) and [manifold's repository](https://github.com/uber/manifold).

| | [Amphion](/tools/open-mmlab-amphion.md) | [manifold](/tools/uber-manifold.md) |
| --- | --- | --- |
| Tagline | Amphion (/æmˈfaɪən/) is a toolkit for Audio, Music, and Speech Generation. Its purpose is to support reproducible research and help junior researchers and engineers get started in the field of audio,  | A model-agnostic visual debugging tool for machine learning |
| Stars | 9,927 | 1,671 |
| Forks | 822 | 115 |
| Open issues | 175 | 83 |
| Language | Python | JavaScript |
| Adopt for | - | - |
| Persona | - | - |
| Runtime | - | - |
| License | MIT | Apache-2.0 |
| Categories | Computer Vision, Inference & Serving, Speech & Audio | Computer Vision |

## Trust and health

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

| | [Amphion](/tools/open-mmlab-amphion.md) | [manifold](/tools/uber-manifold.md) |
| --- | --- | --- |
| Maintenance | Slowing (36%) | Dormant (18%) |
| Days since push | 107d | 521d |
| Open issues (now) | 175 | 83 |
| Full report | [trust report](/tools/open-mmlab-amphion/trust.md) | [trust report](/tools/uber-manifold/trust.md) |

## Choose when

### Choose Amphion if…

- Amphion is primarily Python; manifold is JavaScript.
- License: Amphion is MIT, manifold is Apache-2.0.
- Tags unique to Amphion: audio-generation, audio-synthesis, audioldm, audit.
- Also covers Inference & Serving, Speech & Audio.
- Amphion ships Docker support for self-hosted deployment.

### Choose manifold if…

- manifold is primarily JavaScript; Amphion is Python.
- License: manifold is Apache-2.0, Amphion is MIT.
- Tags unique to manifold: incubation, javascript, machine-learning, visualization.

## When NOT to use Amphion

- Last GitHub push was 108 days ago (slowing maintenance, Mar 25, 2026). Validate activity before betting a new project on Amphion.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.

## When NOT to use manifold

- Last GitHub push was 521 days ago (dormant maintenance, Feb 5, 2025). Validate activity before betting a new project on manifold.

## Common questions

### What is the difference between Amphion and manifold?

Amphion: Amphion (/æmˈfaɪən/) is a toolkit for Audio, Music, and Speech Generation. Its purpose is to support reproducible research and help junior researchers and engineers get started in the field of audio, . manifold: A model-agnostic visual debugging tool for machine learning. See the comparison table for live GitHub stats and shared categories.

### When should I choose Amphion over manifold?

Choose Amphion over manifold when Amphion is primarily Python; manifold is JavaScript; License: Amphion is MIT, manifold is Apache-2.0; Tags unique to Amphion: audio-generation, audio-synthesis, audioldm, audit; Also covers Inference & Serving, Speech & Audio; Amphion ships Docker support for self-hosted deployment.

### When should I choose manifold over Amphion?

Choose manifold over Amphion when manifold is primarily JavaScript; Amphion is Python; License: manifold is Apache-2.0, Amphion is MIT; Tags unique to manifold: incubation, javascript, machine-learning, visualization.

### When should I avoid Amphion?

Last GitHub push was 108 days ago (slowing maintenance, Mar 25, 2026). Validate activity before betting a new project on Amphion. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.

### When should I avoid manifold?

Last GitHub push was 521 days ago (dormant maintenance, Feb 5, 2025). Validate activity before betting a new project on manifold.

### Is Amphion or manifold more popular on GitHub?

Amphion has more GitHub stars (9,927 vs 1,671). Stars measure visibility, not whether either tool fits your constraints.

### Are Amphion and manifold open source?

Yes - both are open-source projects on GitHub (Amphion: MIT, manifold: Apache-2.0).

### Where can I find alternatives to Amphion or manifold?

GraphCanon lists graph-backed alternatives at [Amphion alternatives](/tools/open-mmlab-amphion/alternatives) and [manifold alternatives](/tools/uber-manifold/alternatives) ([Amphion markdown twin](/tools/open-mmlab-amphion/alternatives.md), [manifold markdown twin](/tools/uber-manifold/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/open-mmlab-amphion-vs-uber-manifold.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, Amphion or manifold?

Amphion: Slowing. manifold: Dormant. 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 Amphion and manifold?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Amphion trust report](/tools/open-mmlab-amphion/trust); [manifold trust report](/tools/uber-manifold/trust).

---

**Machine-readable endpoints**

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