Model deployment for AI applications is supported by nndeploy, a framework described as easy to use and high performance.
Open source
24 alternativesKitOps
KitOps packages and versions AI models, datasets, code, and configuration as OCI artifacts.
About KitOps
KitOps is an open source tool for packaging, versioning, and sharing AI/ML projects. It bundles model weights, datasets, code, configuration, and related files into a versioned ModelKit artifact based on OCI standards for storage in a container registry.
The Kit CLI supports ModelKit and ModelPack formats, can generate a Kitfile with kit init, import models from HuggingFace, and push and pull packages. It can be used with Cosign signing, security scans with signed attestations, and CI/CD workflows. Use requires an existing container registry.
Key features
- Packages models, datasets, code, and config as versioned OCI artifacts
- Stores ModelKits in existing container registries
- Imports models from HuggingFace into ModelKits
- Generates Kitfile with kit init command
- Supports ModelKit and ModelPack formats in CLI
- Signs artifacts with Cosign and attaches scan attestations
Best for: Teams that package, version, and deploy AI/ML models using container registries.
Good for
- Open source tool governed by the CNCF
- Uses OCI standards and existing container registries for storage
- CLI supports both ModelKit and ModelPack formats
KitOps at a glance
- Website
- github.com/jozu-ai/kitops
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Platforms
- Linux, Windows
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
KitOps alternatives
Tools and sites you could use instead, ranked by how closely they match.
Valohai provides MLOps tools for comparing, evaluating, and shipping configurations for AI products using specialized models.
Kili Technology provides annotation tools for building datasets to train, fine-tune, and evaluate AI models.
Langtail helps product teams build, test, version, and deploy AI prompts collaboratively.
MLOps framework to package, deploy, monitor and manage thousands of production machine learning models.
Roboflow provides tools to build and deploy computer vision models, from annotation to model deployment.
Freemium
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KitOps FAQ
What can a ModelKit include?
Agents, model weights, MCP servers, datasets, prompts, experiment run results and hyperparameters, metadata, environment configurations, code, and more.
Where are ModelKits stored?
In an existing container registry, using kit push to upload and kit pull to retrieve.
How do you start a new package?
Navigate to the project directory and run kit init . to auto-generate a Kitfile, then pack, push, and pull, or import a model from HuggingFace.
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