Provisioning models determine the availability, lifespan, and pricing of your
instances. If you understand these models, then you can choose the best option
for your workload.
Available provisioning models
When you create a compute instance, you can specify one of the following
provisioning models. If you don't specify a provisioning model, then
Compute Engine uses the standard provisioning model by default.
Based on resource availability, you can immediately create
instances.
You can control when to stop or delete instances.
Based on resource availability, you can immediately create
instances.
You can control when to stop or delete instances. However, you
also allow Compute Engine to stop or delete instances at any
time to reclaim capacity.
After you create a zonal managed instance group (MIG), you request
Compute Engine to add instances with GPUs attached to the
MIG. Compute Engine schedules the provisioning of the
instances based on resource availability.
You can control when to delete instances. However, you can't stop,
suspend, or recreate them. The instances run for up to seven days.
Then, Compute Engine deletes them.
You can request to reserve capacity at a future date for creating
instances with GPUs attached. If Google Cloud approves your request,
then Compute Engine creates a reservation. At the start of
the reservation period, you can consume the reservation by creating
GPU instances that match the reservation.
During the approved reservation period, you can stop, restart,
delete, and recreate instances to consume the reservation as needed.
When the reservation period ends, Compute Engine deletes the
reservation, and stops or deletes any instances that consume the
reservation.
Use cases
Ideal for workloads that require stability and continuous operation,
such as the following workloads:
Web servers
Databases
Enterprise applications
Development and testing
Ideal for workloads that can tolerate interruptions, such as the
following workloads:
Batch processing
High performance computing (HPC)
Continuous integration and continuous deployment (CI/CD)
Data analytics
Media encoding
Online inference
Workloads that require stability and need to run for no more than
seven days, such as the following workloads:
Small model pre-training
Model fine-tuning
HPC simulation
Batch inference
Ideal for workloads that require stability and a specific run time,
such as the following:
For workloads that last up to 90 days:
Model pre-training jobs
Model fine-tuning jobs
HPC simulation workloads
Short-term expected increases in inference workloads
For workloads longer than 90 days:
Training workloads
Inference workloads
Pricing
You incur standard pricing for instances. For more information, see
VM instance pricing.
Most vCPUs, GPUs, and Local SSD are available at a 60-91% discount.
For more information, see
Spot VMs pricing.
Based on the machine family that your instances use, you get up to a
53% discount for vCPUs and GPUs. Additionally, you incur charges based
on how you reserve capacity for creating instances as follows:
You can create instances at any time, as long as your requested
resources are available.
You can create instances at any time, as long as your requested
resources are available.
You can only create instances by creating
resize requests in a MIG. Compute Engine uses
DWS to schedule the provisioning of your requested capacity based on
resource availability. DWS helps you obtain high-demand resources like
GPUs.
You can only create instances after reserving capacity for a future
date. On your requested date, Compute Engine delivers your
requested capacity, which you can then use to create instances. If you
reserve resources using future reservations in calendar mode, then
Compute Engine uses
DWS to provision your requested capacity. DWS helps you obtain
high-demand resources like GPUs.
Instance lifespan
You can control when to stop or delete an instance, except in the
following cases:
If the machine type that the instance uses doesn't support live
migration, then Compute Engine stops your instances during
host
maintenance events.
In rare cases, the instance may stop due to a host error.
You can control when to stop or delete an instance, except in the
following cases:
Compute Engine might stop or delete the instance at any
time to reclaim capacity. This process is called
preemption.
If the machine type that the instance uses doesn't support live
migration, then Compute Engine stops your instances during
host
maintenance events.
In rare cases, the instance may stop due to a host error.
The provisioned instances run for your chosen run duration, which can
be up to seven days. You can't stop, suspend, or recreate instances.
Compute Engine deletes instances when one of the following
happens:
You request to delete instances.
The instances reach the end of their run duration.
You can control when to stop or delete an instance, except in the
following cases:
The automatically created reservation to provision your
requested capacity reaches the end of its committed reservation
period. At that time, Compute Engine deletes the
reservation, and stops or deletes any instances that consume the
reservation.
In rare cases, the instance may stop due to a host error.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-26 UTC."],[],[],null,["# Compute Engine instances provisioning models\n\nLinux Windows\n\n*** ** * ** ***\n\nThis document describes the provisioning models for Compute Engine instances.\nTo learn more about deployment options, see\n[Choose a Compute Engine deployment strategy for your workload](/compute/docs/choose-compute-deployment-option).\n\n*Provisioning models* determine the availability, lifespan, and pricing of your\ninstances. If you understand these models, then you can choose the best option\nfor your workload.\n\nAvailable provisioning models\n-----------------------------\n\nWhen you create a compute instance, you can specify one of the following\nprovisioning models. If you don't specify a provisioning model, then\nCompute Engine uses the standard provisioning model by default.\n\n- Standard\n\n- Spot\n\n- Flex-start ([Preview](/products#product-launch-stages))\n\n- Reservation-bound\n\nThe following table helps you compare the use cases and pricing for each\nprovisioning model:\n\nInstance availability and lifespan\n----------------------------------\n\nThe following table shows you the compute instances availability and lifespan\nfor each provisioning model:\n\nWhat's next\n-----------\n\n- Read an\n [overview of creating Compute Engine instances](/compute/docs/instances/instance-creation-overview).\n\n- To create instances by using the spot provisioning model, see\n [Spot VMs](/compute/docs/instances/spot).\n\n- To create instances by using the flex-start provisioning model, see\n [About resize requests in a MIG](/compute/docs/instance-groups/about-resize-requests-mig).\n\n- To reserve capacity to create instances by using the reservation-bound\n model, see one of the following options:\n\n - [About future reservation requests in calendar mode](/compute/docs/instances/future-reservations-calendar-mode-overview)\n\n - [Reserve capacity in AI Hypercomputer](/ai-hypercomputer/docs/reserve-capacity)"]]