CompreFace vs Nyckel
CompreFace
github.comNyckel
nyckel.comSide by side
| Figure | CompreFace | Nyckel |
|---|---|---|
| Price from | Free | $149/mo |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | Yes | — |
| Web | Yes | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | — |
| Plans published | 2 | 4 |
| Spec score · AI Image Recognition Software | 8.9 (#2) | 7.8 (#19) |
| Spec score · Image Recognition Software | 8.9 (#2) | 7.8 (#14) |
| Deployment | It is delivered as a Docker Compose configuration and can run as a standalone server or be deployed in the cloud. | Nyckel says custom models can be deployed in its secure infrastructure in any AWS, GCP, or Azure region or in the customer's cloud. |
| Integrations | The project invites contributors to add support for other platforms such as Home Assistant or DreamFactory; it does not describe these as built-in integrations on the page. | Nyckel offers a Zapier integration with classify, import, and train actions, and the integration is available to users on any plan. |
| Support | The project directs users to report ideas and bugs on GitHub and offers a community chat link. | The Enterprise plan includes dedicated ML support and consulting. |
| What it does | CompreFace is Exadel’s free, open-source facial-recognition server designed for integration into other systems. | Nyckel provides live API endpoints that turn inputs into structured decisions while handling model selection, training, hosting, monitoring, and continuous improvement. |
Plans
In their own words
CompreFace
CompreFace is a free, open-source face recognition service that provides capabilities through a REST API. It supports face recognition and verification, plus face, landmark and mask detection, head pose detection, age recognition and gender recognition. The project says setup and use do not require prior machine-learning skills. It is packaged as a Docker Compose configuration and can run as a standalone server or in the cloud; listed deployment options also include hybrid use. Setup instructions cover Windows, macOS and Linux and require Docker with Docker Compose or Docker Desktop. The service supports CPU and GPU models, with an x86 processor supporting AVX among the stated requirements. A UI panel and role management let users manage roles and control access to face recognition services. The project names FaceNet and InsightFace among its underlying libraries and links JavaScript, Python and .NET SDK repositories. CompreFace is self-hosted and released under Apache 2.0. The documented quick start uses a release archive and starts the service with docker-compose up -d; the project also points users to GitHub channels and a community chat.
Nyckel
Nyckel provides live API endpoints that turn inputs into structured decisions while handling model selection, training, hosting, monitoring, and ongoing improvement. It supports classification, Box Detect, and Search functions, with image classification, object detection, and OCR listed as capabilities. Endpoints become live when created and can return predictions before labeled examples are added. Each prediction includes a calibrated confidence score from 0.0 to 1.0. Reviewed predictions can become training samples; Nyckel retrains and promotes a model only when it scores better than the current one. A REST API uses bearer-token authentication and exposes endpoints for functions, labels, samples, annotations, and invocation. Zapier provides classify, import, and train actions on every plan. Custom models can be deployed in Nyckel infrastructure across AWS, GCP, or Azure regions, or in a customer cloud. The Free plan includes 100 invokes monthly, up to 200 samples, and five functions.