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Resource Tiers

Reference · Updated Sep 2026

Coming from another cloud?

▸AWS·Instance Types

Instance Typeshigh

  • Fixed predefined configurations only; no custom flavor creation.
  • Extensive families for GPU/HPC/ARM etc.
  • InstanceType as string param in API, not ID reference.
  • Tied to specific hardware generations (Nitro/Xen).
AWS docs ↗
▸Azure·VM sizes

VM sizeshigh

  • Predefined hardware-optimized series (e.g., D-family general purpose) with complex naming (e.g., Standard_D4as_v5), not user-defined vCPU/RAM like OpenStack flavors.
  • Sizes listed via API /providers/Microsoft.Compute/locations/{location}/vmSizes, region-specific availability.
  • Includes accelerator features (GPU, FPGA) baked into sizes, unavailable in basic OpenStack flavors without extensions.
  • Cannot create custom sizes; selection from catalog, limiting flexibility vs OpenStack flavor creation.
Azure docs ↗
▸DigitalOcean·Droplet sizes (plans)

Droplet sizes (plans)high

  • A Droplet must select a predefined “size” bundle (RAM/vCPU/disk/transfer) rather than choosing from an OpenStack flavor catalog that many clouds let you customize/extend at the project level.
  • The size object exposes explicit monthly pricing (price_monthly) and per-hour pricing (price_hourly) in the API response, whereas OpenStack clouds typically separate pricing from the Nova flavor definition.
  • DigitalOcean sizes embed transfer allowance and region availability directly in the size metadata, while OpenStack flavors generally describe compute resources and rely on separate networking/quotas/policies for bandwidth and availability.
  • DigitalOcean size classes are described in the API as categories like Basic, General Purpose, CPU-Optimized, Memory-Optimized, and Storage-Optimized rather than OpenStack’s provider-defined flavor naming/extra-specs approach.
DigitalOcean docs ↗
▸Google Cloud·Machine types

Machine typeshigh

  • Organized by families/series (e.g. N2 general-purpose); OpenStack flavors flat list.
  • Custom types +5% premium for N/E series; no such billing in OpenStack.
  • Naming 'n2-standard-4'; shared-core bursting types absent in OpenStack.
Google Cloud docs ↗
▸Hetzner·Server Types

Server Typeshigh

  • Fixed predefined types (e.g. CX11, CPX31) with shared_vcpu (noisy neighbors) vs dedicated_vcpu.
  • GET /v1/server_types lists all; no custom flavor creation like OpenStack.
  • Includes pricing (hourly/monthly net/gross), included_traffic, architecture (x86/amd64/arm).
  • Resize via change_type action, but limited to compatible types.
Hetzner docs ↗

Resource tiers

Resource tiers are billing packs that set how much compute, memory, and block storage a project subscription includes.

  • You select a tier when you create a project (Compute tile in the portal wizard).
  • Tiers bill monthly.
  • You can upgrade, downgrade, or pause a tier later.
Resource tiervCPUsRAMBlock storagePublic IP
Developer1 shared1 GiB20 GiB1 included
OpenClaw Starter4 shared4 GiB25 GiB1 included
Basic4 dedicated16 GiB50 GiB1 included

Object storage is an add-on you set with the Storage tile or later on the project. Extra public IPs beyond the included address are also add-ons.

All tiers include:

  • AMD EPYC processors (shared or dedicated, depending on the pack)
  • NVMe block storage
  • Subnets, routers, and security groups
  • Outbound data transfer
  • About 0.5 Gbps outbound per 2 vCPUs

Current prices and the custom-package calculator live on the pricing reference and the Quake AI pricing page slider.

Wizard showing Developer selected with shared vCPU, RAM, block storage, and IP slidersClick to zoom
Developer pack in the signup wizard
Wizard showing OpenClaw Starter selected with 4 shared vCPUs and 4 GiB RAMClick to zoom
OpenClaw Starter pack in the signup wizard
Wizard showing Basic selected with 4 dedicated vCPUs, 16 GiB RAM, and 50 GiB block storageClick to zoom
Basic pack in the signup wizard

Dedicated and shared vCPUs#

Every resource tier runs on AMD EPYC processors. You choose dedicated or shared vCPUs based on how much guaranteed performance you need.

Dedicated vCPUs give you exclusive access to those vCPUs. Quake AI sells dedicated vCPUs in units of two, so the smallest dedicated VM is 2 vCPUs. Each dedicated vCPU you purchase can be used as 1 dedicated vCPU or as 4 shared vCPUs across VMs.

Shared vCPUs cost less and suit development, prototyping, and smaller projects. Developer and OpenClaw Starter start on shared vCPUs. Basic starts on dedicated vCPUs and can also host shared vCPUs (up to 16 shared on the default Basic pack).

After you choose your tier and launch the project, you launch dedicated or shared instances from the Console.

Customizable tiers#

You can add and remove vCPUs, memory, block storage, object storage, and additional public IPv4 addresses on a project, within the slider ranges the portal shows for that pack.

Developer plan details#

The Developer plan is the entry-level tier for trying the platform, prototyping, and lightweight workloads.

ResourceIncluded
vCPUs1 shared
RAM1 GiB
Block storage20 GiB NVMe
Object storageAdd-on
NetworkUp to 0.5 Gbps
Public IP1

For current prices, the full plan comparison, and the pricing calculator, see the pricing reference.

When to upgrade from Developer#

Move to OpenClaw Starter when you need more shared vCPUs and RAM (4 shared vCPUs, 4 GiB) on the same shared-CPU model.

Move to Basic when you need dedicated vCPUs, 16 GiB RAM, and 50 GiB included block storage.

For a custom mix, use the pricing calculator slider.

Moving an existing VM to a dedicated-vCPU flavor does not require you to rebuild it: see How to resize a Quake AI VM to a dedicated-CPU plan.

Tutorials sized for Developer Plan#

Tutorials in the Quickstart include Developer Plan callouts that note swap requirements, memory limits, and alternative paths if you outgrow the tier. Look for the "Developer Plan" callout in:

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