# Sonos, Inc. — developer ecosystem report

> The Wireless Hi-Fi system

- GitHub org: `sonos`
- Category: ai
- Overall score: 41.0 / 100
- Overall rank: #431
- Last refreshed: 2026-08-15

## Pillar scores

| Pillar | Score / 100 | Rank | Weight in overall |
| --- | --- | --- | --- |
| Code & Polish | 48.0 | #502 | ~22% |
| Education | 63.0 | #492 | ~18% |
| AI readiness | 33.0 | #423 | part of Reach |
| Builder experience | 0.0 | #1 | ~12% |
| Community | 42.0 | #312 | ~16% |
| Reach | 39.0 | #584 | ~18% |
| Momentum | 9.0 | #803 | ~14% |

## Links

- GitHub: https://github.com/sonos
- Website: https://www.sonos.com
- Docs: https://docs.sonos.com

## Public GitHub totals

| Metric | Value |
| --- | --- |
| Repos analyzed | 12 |
| Stars | 4,751 |
| Forks | 618 |
| Open issues | 225 |
| Contributors | — |

## Top repositories

| Repo | Stars | Language | Description |
| --- | --- | --- | --- |
| [tract](https://github.com/sonos/tract) | 3,029 | Rust | Tiny, no-nonsense, self-contained, Tensorflow and ONNX inference |
| [nlu-benchmark](https://github.com/sonos/nlu-benchmark) | 510 | — | — |
| [dinghy](https://github.com/sonos/dinghy) | 417 | Rust | Easier cross-compilation for phones and single boards computers |
| [pyFLAC](https://github.com/sonos/pyFLAC) | 145 | C | Real-time lossless audio compression in Python |
| [keyword-spotting-research-datasets](https://github.com/sonos/keyword-spotting-research-datasets) | 141 | — | — |
| [rustling-ontology](https://github.com/sonos/rustling-ontology) | 140 | Rust | Ontology for rustling |
| [ffi-convert-rs](https://github.com/sonos/ffi-convert-rs) | 114 | Rust | Easier and safer interface between Rust, C, and other languages |
| [rustling](https://github.com/sonos/rustling) | 82 | Rust | Rust implementation of Duckling |
| [api-web-sample-app](https://github.com/sonos/api-web-sample-app) | 51 | JavaScript | Sample app to showcase how third party developers can integrate with Sonos. |
| [spoken-language-understanding-research-datasets](https://github.com/sonos/spoken-language-understanding-research-datasets) | 51 | Python | — |
| [torch-to-nnef](https://github.com/sonos/torch-to-nnef) | 21 | Python | Any PyTorch model to NNEF exchange format |
| [automatic-data-generation](https://github.com/sonos/automatic-data-generation) | 18 | Python | Pytorch implementation of experiments described in "Conditioned Text Generation with Transfer for Closed-Domain Dialogue |

## Methodology

Scores are computed from public signals only (GitHub, package registries, docs sites, community platforms). Pillar definitions: https://www.smoower.com/docs.md

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