ModelKit Overview

ModelKit is a standardized, OCI-compliant packaging format for AI/ML projects.

It bundles everything your model needs — datasets, training code, config files, documentation, and the model itself — into a single shareable artifact.

Use ModelKits to version, share, and deploy AI models across teams and environments using familiar DevOps tools like DockerHub, GitHub Packages, or private registries.

➡️ Get started with ModelKits in under 15 minutes ➡️ See how security-focused teams use ModelKits

🔑 Key Features

• OCI-compliant and tool-friendly Store, tag, and version ModelKits in any container registry — no custom infrastructure needed.

• Selective unpacking Unpack only the parts you need (e.g. just the dataset or model weights) to speed up pipelines and reduce compute overhead.

• No duplication for shared assets Reuse datasets or configs across multiple kits without bloating storage.

• Familiar versioning and tagging Use registry-native tags (e.g. :latest, :prod, :rollback) to track model state and history.

• Built for ML workflows Supports AI-specific needs like serialized model handling, reproducible training snapshots, and data lineage.

• Streamlined collaboration Teams can pull, inspect, and repack models just like container images — making it easier to collaborate across roles and environments.

⚡ Why It Matters

ModelKit simplifies the messy handoff between data scientists, engineers, and operations. It gives teams a common, versioned package that works across clouds, registries, and deployment setups — without reinventing storage or delivery.

It’s more than a format — it’s a building block for secure, reproducible AI.

🔄 ModelPack Format Support

KitOps supports both ModelKit and ModelPack artifact formats:

• ModelKit (default) — KitOps' native format with integrated Kitfile configuration
• ModelPack — The CNCF model-spec format for vendor-neutral AI/ML interchange

Using ModelPack Format

To pack artifacts in ModelPack format, use the --use-model-pack flag:

kit pack . --use-model-pack -t registry/repo:tag

Compatibility

All Kit CLI commands work transparently with both formats:

• kit pull — Works with ModelKit and ModelPack artifacts
• kit unpack — Extracts contents from either format
• kit inspect — Shows manifests for both types
• kit list — Displays artifacts regardless of format
• kit push — Pushes any supported artifact type

When you pack with --use-model-pack, your Kitfile is preserved as a manifest annotation, ensuring you can still retrieve and use it with Kit commands.

Note: ModelPack artifacts created by other tools (not Kit) may not include a Kitfile. Kit can still unpack these artifacts if they use the org.cncf.model.filepath annotation to specify file paths.

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