# Edge Microvisor Toolkit Versions

Edge Microvisor Toolkit is available in several pre-configured versions that
serve different purposes. Some are published as binaries, others are available
from a custom build. This document will help you select the version that best
suits your needs. To do so, check out:

## How to select the right EMT

![emt-version-deployment](../assets/emt-version-deployment.drawio.svg)

## How EMT differs between versions

| Version | Real Time | Stable Kernel | [Next Kernel](../emt-architecture-overview.md#next-kernel) |
|--------|---------|-------------|------|
| [**Standalone (Immutable)**](https://github.com/open-edge-platform/edge-microvisor-toolkit-standalone-node) | Available for opt-in | ✓ | ✓ |
| [**Developer Node (Mutable)**](../emt-architecture-overview.md#developer-node-mutable-iso-image) | Optional | ✓ | ✓ |
| [**EMT for EMF**](../tutorials/emt-deployment-edge-orchestrator.md) | Available for opt-in | ✓ | ✓ |
| [**Bootkit**](../emt-bootkit.md) | - | ✓ | – |

## How usage scenarios affect EMT setup

::::{tab-set}
:::{tab-item} Real Time & Deterministic
:sync: tab1
\
Run latency-sensitive workloads with guaranteed bounded jitter and repeatable
execution timelines across one or more hosts, maintainable under steady-state
and failure-recovery conditions.

*Primary outcomes:*

- Bounded end-to-end latency & jitter
- Repeatable scheduling windows under load
- Cross-host timing consistency for distributed stages
- Fast, predictable recovery without violating SLOs

*Technology areas:*

- [PREEMPT_RT kernel](../emt-architecture-overview.md#preempt-rt-kernel)
- [Resource Director Technologies](../emt-architecture-overview.md#resource-director-technology)
- [Intel GPU RT](../emt-architecture-overview.md#intel-device-plugins-for-kubernetes)
- [CPU & Scheduler Isolation](../emt-architecture-overview.md#isolcpuslist)
- [Memory Determinism](../emt-architecture-overview.md#preempt-rt-kernel)
- [Network Determinism (TSN)](../emt-architecture-overview.md#time-sensitive-networking-support)
- Time & Clocks

*Kernel patchsets (quilts):*

- [PREEMPT_RT](../architecture/emt-extensions-and-patches.md#preempt_rt)
- [Time-Sensitive Networking](../architecture/emt-extensions-and-patches.md#time-sensitive-networking-tsn)

:::
:::{tab-item} Virtual Machines (Kubernetes, shared GPUs)
:sync: tab2
\
Run multiple virtual machines on Kubernetes that concurrently share one or more
physical GPUs, with predictable fairness, isolation, and policy-driven placement—using
a KubeVirt stack extended for GPU sharing.

*Primary outcomes:*

- Stable, repeatable GPU performance per VM under contention
- Hard/soft sharing policies (fair-share, priority tiers, or quotas)
- Safe isolation between tenants/VMs (memory, contexts, resets)
- Schedulable resources with clear admission signals (no surprise fails)
- Operational guardrails: health checks, graceful drain/eviction, rollback

*Technology areas:*

- [SRIOV](./deployment/emt-vm-host.md)
- [Intel GPU](../emt-system-requirements.md#discrete-gpu)
- [kubevirt](https://github.com/open-edge-platform/edge-microvisor-toolkit-standalone-node/blob/main/standalone-node/docs/user-guide/desktop-virtualization-image-guide.md)
- [Host virtualization](./deployment/emt-vm-host.md)
- [Intel GPU device plugin](../emt-architecture-overview.md#intel-device-plugins-for-kubernetes)

*Kernel patchsets (quilts):*

- [SR-IOV](../architecture/emt-extensions-and-patches.md#sr-iov)
- [DRM](../architecture/emt-extensions-and-patches.md#drm) 


:::
:::{tab-item} AI & Vision Systems
:sync: tab3
\
Enable AI inference and computer-vision workloads on edge nodes using Intel GPU
and NPU acceleration, exposing unified hardware-assisted pipelines through
standard APIs and user-space libraries.

*Primary outcomes:*

- Efficient execution of deep-learning and vision inference on-device without
  cloud dependency
- Unified GPU/NPU compute abstraction for developers (OpenVINO backend,
  media pipelines)
- Deterministic frame-rate and latency for multi-stream analytics workloads
  (e.g., camera ingest)
- Seamless integration with containers or pods, including dynamic device
  discovery and sharing
- Stable ABI/API interface across [OS updates](../architecture/emt-updates.md)
  and driver versions

*Technology areas:*

- [Edge AI packages](https://eci.intel.com/docs/3.3/packages_list.html)
- [OpenVino](https://docs.openvino.ai)
- [Intel GPU and NPU drivers](https://docs.openvino.ai/2025/openvino-workflow/running-inference/inference-devices-and-modes.html)
- [Intel GPU device plugin](../emt-architecture-overview.md#intel-device-plugins-for-kubernetes)

:::
::::

## How to build your own version of EMT

You can create your own custom version of Edge Microvisor Toolkit by following
[the guide](./emt-building-howto.md). You can also try and learn how to
[build your own solution and deploy it on edge](./emt-build-and-deploy.md).