Subscription Information IaaS Credit Rates, Subscription Types, Overage Policies, Cloud PC Flex Credit Rates, DaaS Flex Credit Rates IaaS Credit Rates Multi-tenant customers deploying their workloads on Dizzion-provided public cloud subscriptions (AWS, Google Cloud Platform, and Microsoft Azure) can pay for their public cloud usage (VM and disk) in the form of IaaS Credits . IaaS Credit rates vary based on public cloud and instance type running the VM. More powerful instances consume more credits. Please see tables below for current rates. Note that instance rates are valid across all supported public cloud regions globally. For pay-as-you-go customers, IaaS Credits consumed during the previous billing cycle are charged at a price of $0.0125 per credit . Term customers may also pre-pay their IaaS Credits in bundles of 10,000 credits for $100 per bundle . To request support for new instance types, please submit a support ticket detailing the requested instances and your use case. Support for new instance types will be added based on demand, availability, performance, and compatibility. Instance Types Instance Name Instance Type vCPUs RAM GPU Provider Credits Air 4GB t2.medium 1 4 GB   AWS 12 Air 4GB (T3) t3.medium 1 4 GB   AWS 20 Air 8GB t2.large 1 8 GB   AWS 24 Air 8GB (T3) t3.large 1 8 GB   AWS 32 Air 16GB (T3) t3.xlarge 2 16 GB   AWS 54 Air 4GB (AMD) t3a.medium 4 4 GB   AWS 20 Air 8GB (AMD) t3a.large 4 8 GB   AWS 28 Air 16GB (AMD) t3a.xlarge 8 16 GB   AWS 50 Air 32GB (AMD) t3a.2xlarge 16 32 GB   AWS 90 Pro 16GB g2.2xlarge 4 16 GB 1 GPU AWS   Pro 16GB (G4) g4dn.xlarge 4 16 GB 1 GPU AWS 125 Pro 32GB g3s.xlarge 2 32 GB 1 GPU AWS 170 Pro 32GB (G4) g4dn.2xlarge 8 32 GB 1 GPU AWS 170 Pro 122GB g3.4xlarge 8 122 GB 1 GPU AWS 340 Pro 64GB (G4) g4dn.4xlarge 16 64 GB 1 GPU AWS 340 Pro 128GB (G4) g4dn.8xlarge 32 128 GB 1 GPU AWS 680 Pro 16GB (AMD) g4ad.xlarge 4 16 GB 1 GPU AWS 80 Pro 32GB (AMD) g4ad.2xlarge 8 32 GB 1 GPU AWS 110 Pro 64GB (AMD) g4ad.4xlarge 16 64 GB 1 GPU AWS 220 Pro 128GB (AMD) g4ad.8xlarge 32 128 GB 2 GPUs AWS 440 Pro 256GB (AMD) g4ad.16xlarge 64 256 GB 4 GPUs AWS 880 Pro 192GB (G4) g4dn.12xlarge 24 192 GB 4 GPUs AWS 1150 Pro 256GB (G4) g4dn.16xlarge 32 256 GB 1 GPU AWS 1350 Pro 16GB (G5) g5.xlarge 2 16 GB 1 GPU AWS 170 Pro 32GB (G5) g5.2xlarge 4 32 GB 1 GPU AWS 220 Pro 64GB (G5) g5.4xlarge 8 64 GB 1 GPU AWS 340 Pro 128GB (G5) g5.8xlarge 16 128 GB 1 GPU AWS 560 Edge 8GB c4.xlarge 2 7.5 GB   AWS 60 Edge 16GB m4.xlarge 2 16 GB   AWS 60 Edge 32GB c4.4xlarge 8 32 GB   AWS 240 Edge 32GB (R5) r5.xlarge 4 32 GB   AWS 70 Edge 64GB (Z1D) z1d.2xlarge 8 64 GB   AWS 160 Edge 64GB m5a.4xlarge 16 64 GB   AWS 220 Edge 8GB (M6) m6i.large 2 8 GB   AWS 28 Edge 16GB (M6) m6i.xlarge 4 16 GB   AWS 56 Edge 32GB (M6) m6i.2xlarge 8 32 GB   AWS 112 Edge 64GB (M6) m6i.4xlarge 16 64 GB   AWS 224 Edge 4GB (C6) c6i.large 2 4 GB   AWS 28 Edge 8GB (C6) c6i.xlarge 4 8 GB   AWS   Edge 16GB (C6) c6i.2xlarge 8 16 GB   AWS 112 Edge 32GB (C6) c6i.4xlarge 16 32 GB   AWS 224 Edge 64GB (C6) c6i.8xlarge 32 64 GB   AWS 448 Edge 4GB (C7) c7i.large 2 4 GB   AWS 30 Edge 8GB (C7) c7i.xlarge 4 8 GB   AWS 60 Edge 16GB (C7) c7i.2xlarge 8 16 GB   AWS 120 Edge 32GB (C7) c7i.4xlarge 16 32 GB   AWS 240 Edge 64GB (C7) c7i.8xlarge 32 64 GB   AWS 480 Edge 8GB (M7) m7i.large 2 8 GB   AWS 30 Edge 16GB (M7) m7i.xlarge 4 16 GB   AWS 60 Edge 32GB (M7) m7i.2xlarge 8 32 GB   AWS 120 Edge 64GB (M7) m7i.4xlarge 16 64 GB   AWS 240 Pro 16GB (G6) g6.xlarge 4 16 GB 1 GPU AWS 190 Pro 32GB (G6) g6.2xlarge 8 32 GB 1 GPU AWS 220 Pro 64GB (G6) g6.4xlarge 16 64 GB 1 GPU AWS 360 Pro 128GB (G6) g6.8xlarge 32 128 GB 1 GPU AWS 580 Pro 192GB (G6) g6.12xlarge 48 192 GB 4 GPUs AWS 1300 Pro 256GB (G6) g6.16xlarge 64 256 GB 1 GPU AWS 1150 Pro 256GB (GR6) gr6.8xlarge 32 256 GB 1 GPU AWS 650 Air 4GB D1_V2 1 4 GB   Azure 12 Air 4GB (A2 v2) A2_V2 2 4 GB   Azure 20 Air 8GB D2_V2 2 8 GB   Azure 24 Air 8GB (D2 v3) D2_v3 2 8 GB   Azure 30 Air 8GB (D2s v3) D2s_v3 2 8 GB   Azure 30 Air 8GB (D2ds v5) D2ds_v5 2 8 GB   Azure 32 Air 16GB D4_v3 4 16 GB   Azure 60 Air 16GB (D4s_v3) D4s_v3 4 16 GB   Azure 60 Air 16GB (D4ds v5) D4ds_v5 4 16 GB   Azure 64 Pro 56GB NV6 6 56 GB 1 GPU Azure 150 Pro 224GB NV24 24 224 GB 4 GPUs Azure 600 Pro 14GB (NV v4) NV4as_v4 4 14 GB 1/8 GPU Azure 70 Pro 28GB (NV v4) NV8as_v4 8 28 GB 1/4 GPU Azure 140 Pro 56GB (NV v4) NV16as_v4 16 56 GB 1/2 GPU Azure 280 Pro 112GB (NV v4) NV32as_v4 32 112 GB 1 GPU Azure 560 Pro 55GB (NV6 A10v5) NV6ads_A10_v5 6 55 GB 1/6 GPU Azure 125 Pro 110GB (NV12 A10v5) NV12ads_A10_v5 12 110 GB 1/3 GPU Azure 250 Pro 220GB (NV18 A10v5) NV18ads_A10_v5 18 220 GB 1/2 GPU Azure 450 Pro 440GB (NV36 A10v5) NV36ads_A10_v5 36 440 GB 1 GPU Azure 850 Edge 8GB F4 4 8 GB   Azure 60 Edge 32GB E4_V3 2 32 GB   Azure 80 Edge 64GB (E8 v4) E8_v4 8 64 GB   Azure 160 Edge 128GB (E16 v4) E16_v4 16 128 GB   Azure   Edge 256GB (E32 v4) E32_v4 32 256 GB   Azure   Pro 122GB (v3) NV12_v3 12 122 GB 1 GPU Azure 300 Pro 224GB (v3) NV24_v3 24 224 GB 2 GPUs Azure 600 Pro 448GB (v3) NV48_v3 48 448 GB 4 GPUs Azure 1200 Pro 28GB (NCas T4) NC4as_T4_v3 4 28 GB 1 GPU Azure 140 Pro 56GB (NCas T4) NC8as_T4_v3 8 56 GB 1 GPU Azure 220 Pro 110GB (NCas T4) NC16as_T4_v3 16 110 GB 1 GPU Azure 360 Pro 440GB (NCas T4) NC64as_T4_v3 64 440 GB 4 GPUs Azure 1440 Air 4GB D1_V2 1 4 GB   Azure 12 Pro 56GB NV6 6 56 GB 1 GPU Azure 150 Pro 224GB NV24 24 224 GB 4 GPUs Azure   Air 8GB n1-standard-2-Windows 2 8 GB   GCP 30 Air 16GB n1-standard-4-Windows 4 15 GB   GCP 60 Air 16GB (N2) n2-standard-4-Windows 4 15 GB   GCP 40 Air 8GB (n2d-standard) n2d-standard-2-Windows 2 8 GB   GCP 28 Air 16GB (n2d-standard) n2d-standard-4-Windows 4 15 GB   GCP 56 Air 30GB (n2d-standard) n2d-standard-8-Windows 8 30 GB   GCP 112 Air 8GB (E2) e2-standard-2-Windows 2 8 GB   GCP 24 Air 16GB (E2) e2-standard-4-Windows 4 16 GB   GCP 48 Pro 16GB n1-standard-4-GPU-P4-Windows 4 15 GB 1 GPU GCP 150 Pro 60GB n1-standard-16-GPU-P4-Windows 16 60 GB 1 GPU GCP 300 Pro 8GB (T4) n1-standard-2-GPU-T4-Windows 2 8 GB 1 GPU GCP 105 Pro 16GB (T4) n1-standard-4-GPU-T4-Windows 4 30 GB 1 GPU GCP 130 Pro 30GB (T4) n1-standard-8-GPU-T4-Windows 8 30 GB 1 GPU GCP 185 Pro 60GB (T4) n1-standard-16-GPU-T4-Windows 16 60 GB 1 GPU GCP 240 Pro 240GB (4xT4) n1-standard-64-GPU-4-T4-Windows 64 240 GB 4 GPUs GCP 1250 Pro 16GB (L4) g2-standard-4-Windows 4 16 GB 1 GPU GCP 140 Pro 32GB (L4) g2-standard-8-Windows 8 32 GB 1 GPU GCP 180 Pro 64GB (L4) g2-standard-16-Windows 16 64 GB 1 GPU GCP 250 Edge 8GB n1-highcpu-8-Windows 8 7.2 GB   GCP 100 Edge 26GB n1-highmem-4-Windows 4 26 GB   GCP 70 Edge 104GB n1-highmem-16-Windows 16 104 GB   GCP 280 Edge 208GB n1-highmem-32-Windows 32 208 GB   GCP 560 Air 10GB (BX3D) bx3d-2x10 2 10 GB   IBM 25 Air 20GB (BX3D) bx3d-4x20 4 20 GB   IBM 45 Air 40GB (BX3D) bx3d-8x40 8 40 GB   IBM 90 Air 5GB (CX3D) cx3d-2x5 2 5 GB   IBM 25 Air 10GB (CX3D) cx3d-4x10 4 10 GB   IBM 45 Air 20GB (CX3D) cx3d-8x20 8 20 GB   IBM 85 Pro 80GB (GX3) gx3-16x80x1l4 16 80 GB 1 GPU* IBM 250 Pro 120GB (GX3) gx3-24x120x1l40s 24 120 GB 1 GPU** IBM 565 Air 8GB (CX2) cx2-4x8 4 8 GB   IBM 40 Air 16GB (CX2) cx2-8x16 8 16 GB   IBM 80 Air 32GB (CX2) cx2-16x32 16 32 GB   IBM 155 Air 8GB (BX2) bx2-2x8 2 8 GB   IBM 25 Air 16GB (BX2) bx2-4x16 4 16 GB   IBM 45 Air 32GB (BX2) bx2-8x32 8 32 GB   IBM 85 Air 64GB (BX2) bx2-16x64 16 64 GB   IBM 165 Air 8GB (BX2A) bx2a-2x8 2 8 GB   IBM 25 Air 16GB (BX2A) bx2a-4x16 4 16 GB   IBM 45 Air 32GB (BX2A) bx2a-8x32 8 32 GB   IBM 85 Air 64GB (BX2A) bx2a-16x64 16 64 GB   IBM 165 Subscription Types and Overage Policies Subscription Subscription Types Customers wishing to subscribe to Frame (Commercial) may choose from one of the following two subscription types: Named user subscriptions Per VM subscriptions Minimum subscription requirements: Cloud PC Complete: 50 users/VMs DaaS: 50 users/VMs Cloud PC Core: 25 users/VMs Named User Subscription Named user (NU) subscriptions are based on the number of unique users that log into Frame (across all Organizations and across all Accounts within a customer's tenant) during a Monthly Billing Cycle (MBC). For each MBC, the subset of unique users can be different. In Frame, a unique user is defined as a user who has authenticated to a specific, customer-configured identity provider with an email address. If the customer configures two identity providers and the user logs into Frame using both identity providers (even with the same email address) in a MBC, the user will be counted as two unique users. As a best practice, customers who purchase named user subscriptions should have each user authenticate to only one identity provider to access Frame. Otherwise, if a user authenticates to more than one identity provider (even using the same email address), customers risk having that user consume more than one named user subscription in a MBC. Per VM Subscription Per VM subscriptions define the maximum number of users that can connect concurrently to Frame workload VMs in a Monthly Billing Cycle (MBC). Since each user is assigned their own non-persistent workload VM for the life of their session or a dedicated persistent desktop, the maximum number of concurrent user subscriptions is equal to the maximum number of workload VMs provisioned in all test and production pools in all Frame Accounts, under all Organizations for the customer. Overages Customers may choose to exceed their pre-paid subscription commitments during a Monthly Billing Cycle (MBC). If this occurs, Frame will invoice the customer for this “overage.” This page discusses how Frame determines whether the customer has incurred overage during an MBC. Instructions for paying the overage can be found at the bottom of the page. Named User At the end of each MBC, Frame calculates the number of unique named users who have logged into Frame during the MBC. The difference between the actual number of unique users and the number of named user subscriptions purchased, if greater than 0, is the named user subscription overage that will be billed to the customer. If the customer purchased via credit card, the user subscription overage will be billed to the credit card on file at the “pay as you go” rate. If the customer purchased via purchase order, then Frame will invoice the customer for the named user subscription overage at the named user subscription list price. Per VM At the end of each MBC, Frame computes the sum of all test and production pool “max” Default Capacity values set in all Frame accounts, under all Organization entities, for the customer's tenant. Overage is defined the difference between the sum of all test and production pool max values and per VM subscriptions purchased. If this value is greater than 0, then Frame will invoice the customer for the per VM subscription overage at the per VM subscription list price. Microsoft RDS SAL For customers who choose to purchase Microsoft Remote Desktop Services Subscriber Access Licenses (RDS SALs) from Frame, at the end of each MBC, Frame calculates the number of unique named users who have logged into Frame during the MBC. The difference between the actual number of unique users and the number of Microsoft RDS SALs purchased, if greater than 0, is the Microsoft RDS SAL overage that will be billed to the customer. If the customer purchased named user subscriptions via credit card, the Microsoft RDS SAL overage will be included as part of the named user subscription overage and billed to the credit card on file at the “pay as you go” rate. If the customer purchased via purchase order, then Frame will invoice the customer for the Microsoft RDS SAL overage at the RDS SAL list price. IaaS Credits For customers who purchase Frame IaaS Credits to run their workloads on Frame-managed public cloud infrastructure subscriptions, at the end of each MBC, Frame calculates the total amount of IaaS Credits used and deducts the credits from the customer's IaaS Credit balance. If the customer's IaaS Credit balance goes below zero credits, the IaaS Credit overage will be billed to the customer. If the customer purchased via credit card, the overage will be billed to the credit card on file at the “pay as you go” rate. If the customer purchased via purchase order, then Frame will invoice the customer for the IaaS Credit overage at the IaaS Credit list price. Frame IaaS Credit consumption rates and specifications for each instance type and storage by IaaS provider can be found on our Pricing page . Paying for Overages You will receive an overage invoice direct from Dizzion with payment instructions. Cloud PC Flex Credit Rates Flex Credits offer a consumption-based pricing model that gives you full freedom to scale, resize, and reallocate desktops without modifying your contract. Choose from prepaid annual commit, monthly pay annual commit, or no-commit options.  Flex Credit rates vary based on public cloud, region, size of the Cloud PC, and Core vs Complete. See sections below for more details.  To calculate estimated Flex Credits required, find the appropriate Cloud PC product in the desired Cloud Provider and Region, then multiply the Flex Credit price by the number of VMs. Repeat this step for each applicable Cloud PC product and Add-On products, then add the values together to get your total monthly Flex Credit budget. For prepaid annual commit, multiply by 12.  Example: AWS Workspaces Core > US East > Standard - 4x16-8050 (Core) = 63 credits per VM per month for 50 VMs = 3,150 credits per month x 12 months = 37,800 credits annually  Dizzion Halo at 15 credits per user per month for 50 users = 750 credits per month x 12 months = 9,000 credits annually 37,800 + 9,000 = 46,800 credits annually  AWS Workspaces Core Region Name  vCPU Memory (GB) GPU Root Volume (GB) User Volume (GB) Cloud PC Core - Flex Credit Price (Per VM Per Month) Cloud PC Complete - Flex Credit Price (Per VM Per Month) NA - US (East) Lite - 2x8-8010 2 8 - 80 10 45 65 NA - US (East) Lite - 2x8-8050 2 8 - 80 50 46 66 NA - US (East) Lite - 2x8-80100 2 8 - 80 100 48 68 NA - US (East) Lite - 2x8-175100 2 8 - 175 100 52 72 NA - US (East) Standard - 4x16-8010 4 16 - 80 10 62 82 NA - US (East) Standard - 4x16-8050 4 16 - 80 50 63 83 NA - US (East) Standard - 4x16-80100 4 16 - 80 100 64 84 NA - US (East) Standard - 4x16-175100 4 16 - 175 100 67 87 NA - US (East) Power - 8x32-8010 8 32 - 80 10 99 119 NA - US (East) Power - 8x32-8050 8 32 - 80 50 101 121 NA - US (East) Power - 8x32-80100 8 32 - 80 100 104 124 NA - US (East) Power - 8x32-175100 8 32 - 175 100 108 128 NA - US (East) Pro-GPU - 4x16-100100 4 16 1 NVIDIA T4 100 100 370 390 NA - US (East) Max-GPU - 16x64-100100 16 64 1 NVIDIA T4 100 100 648 668 NA - US (West) Lite - 2x8-8010 2 8 - 80 10 45 65 NA - US (West) Lite - 2x8-8050 2 8 - 80 50 46 66 NA - US (West) Lite - 2x8-80100 2 8 - 80 100 48 68 NA - US (West) Lite - 2x8-175100 2 8 - 175 100 52 72 NA - US (West) Standard - 4x16-8010 4 16 - 80 10 62 82 NA - US (West) Standard - 4x16-8050 4 16 - 80 50 63 83 NA - US (West) Standard - 4x16-80100 4 16 - 80 100 64 84 NA - US (West) Standard - 4x16-175100 4 16 - 175 100 67 87 NA - US (West) Power - 8x32-8010 8 32 - 80 10 99 119 NA - US (West) Power - 8x32-8050 8 32 - 80 50 101 121 NA - US (West) Power - 8x32-80100 8 32 - 80 100 104 124 NA - US (West) Power - 8x32-175100 8 32 - 175 100 108 128 NA - US (West) Pro-GPU - 4x16-100100 4 16 1 NVIDIA T4 100 100 370 390 NA - US (West) Max-GPU - 16x64-100100 16 64 1 NVIDIA T4 100 100 648 668 NA - Canada Lite - 2x8-8010 2 8 - 80 10 47 67 NA - Canada Lite - 2x8-8050 2 8 - 80 50 50 70 NA - Canada Lite - 2x8-80100 2 8 - 80 100 53 73 NA - Canada Lite - 2x8-175100 2 8 - 175 100 58 78 NA - Canada Standard - 4x16-8010 4 16 - 80 10 66 86 NA - Canada Standard - 4x16-8050 4 16 - 80 50 68 88 NA - Canada Standard - 4x16-80100 4 16 - 80 100 71 91 NA - Canada Standard - 4x16-175100 4 16 - 175 100 73 93 NA - Canada Power - 8x32-8010 8 32 - 80 10 112 132 NA - Canada Power - 8x32-8050 8 32 - 80 50 115 135 NA - Canada Power - 8x32-80100 8 32 - 80 100 119 139 NA - Canada Power - 8x32-175100 8 32 - 175 100 127 147 NA - Canada Pro-GPU - 4x16-100100 4 16 1 NVIDIA T4 100 100 411 431 NA - Canada Max-GPU - 16x64-100100 16 64 1 NVIDIA T4 100 100 724 744 AP - Mumbai Lite - 2x8-8010 2 8 - 80 10 56 76 AP - Mumbai Lite - 2x8-8050 2 8 - 80 50 58 78 AP - Mumbai Lite - 2x8-80100 2 8 - 80 100 60 80 AP - Mumbai Lite - 2x8-175100 2 8 - 175 100 66 86 AP - Mumbai Standard - 4x16-8010 4 16 - 80 10 92 112 AP - Mumbai Standard - 4x16-8050 4 16 - 80 50 93 113 AP - Mumbai Standard - 4x16-80100 4 16 - 80 100 95 115 AP - Mumbai Standard - 4x16-175100 4 16 - 175 100 97 117 AP - Mumbai Power - 8x32-8010 8 32 - 80 10 128 148 AP - Mumbai Power - 8x32-8050 8 32 - 80 50 131 151 AP - Mumbai Power - 8x32-80100 8 32 - 80 100 134 154 AP - Mumbai Power - 8x32-175100 8 32 - 175 100 138 158 AP - Mumbai Pro-GPU - 4x16-100100 4 16 1 NVIDIA T4 100 100 557 577 AP - Mumbai Max-GPU - 16x64-100100 16 64 1 NVIDIA T4 100 100 983 1003 AP - Seoul Lite - 2x8-8010 2 8 - 80 10 52 72 AP - Seoul Lite - 2x8-8050 2 8 - 80 50 55 75 AP - Seoul Lite - 2x8-80100 2 8 - 80 100 58 78 AP - Seoul Lite - 2x8-175100 2 8 - 175 100 63 83 AP - Seoul Standard - 4x16-8010 4 16 - 80 10 72 92 AP - Seoul Standard - 4x16-8050 4 16 - 80 50 75 95 AP - Seoul Standard - 4x16-80100 4 16 - 80 100 77 97 AP - Seoul Standard - 4x16-175100 4 16 - 175 100 80 100 AP - Seoul Power - 8x32-8010 8 32 - 80 10 112 132 AP - Seoul Power - 8x32-8050 8 32 - 80 50 116 136 AP - Seoul Power - 8x32-80100 8 32 - 80 100 119 139 AP - Seoul Power - 8x32-175100 8 32 - 175 100 124 144 AP - Seoul Pro-GPU - 4x16-100100 4 16 1 NVIDIA T4 100 100 402 422 AP - Seoul Max-GPU - 16x64-100100 16 64 1 NVIDIA T4 100 100 707 727 AP - Singapore Lite - 2x8-8010 2 8 - 80 10 56 76 AP - Singapore Lite - 2x8-8050 2 8 - 80 50 58 78 AP - Singapore Lite - 2x8-80100 2 8 - 80 100 60 80 AP - Singapore Lite - 2x8-175100 2 8 - 175 100 66 86 AP - Singapore Standard - 4x16-8010 4 16 - 80 10 92 112 AP - Singapore Standard - 4x16-8050 4 16 - 80 50 93 113 AP - Singapore Standard - 4x16-80100 4 16 - 80 100 95 115 AP - Singapore Standard - 4x16-175100 4 16 - 175 100 97 117 AP - Singapore Power - 8x32-8010 8 32 - 80 10 128 148 AP - Singapore Power - 8x32-8050 8 32 - 80 50 131 151 AP - Singapore Power - 8x32-80100 8 32 - 80 100 134 154 AP - Singapore Power - 8x32-175100 8 32 - 175 100 138 158 AP - Singapore Pro-GPU - 4x16-100100 4 16 1 NVIDIA T4 100 100 493 513 AP - Singapore Max-GPU - 16x64-100100 16 64 1 NVIDIA T4 100 100 871 891 AP - Sydney Lite - 2x8-8010 2 8 - 80 10 52 72 AP - Sydney Lite - 2x8-8050 2 8 - 80 50 54 74 AP - Sydney Lite - 2x8-80100 2 8 - 80 100 56 76 AP - Sydney Lite - 2x8-175100 2 8 - 175 100 62 82 AP - Sydney Standard - 4x16-8010 4 16 - 80 10 83 103 AP - Sydney Standard - 4x16-8050 4 16 - 80 50 85 105 AP - Sydney Standard - 4x16-80100 4 16 - 80 100 87 107 AP - Sydney Standard - 4x16-175100 4 16 - 175 100 89 109 AP - Sydney Power - 8x32-8010 8 32 - 80 10 115 135 AP - Sydney Power - 8x32-8050 8 32 - 80 50 117 137 AP - Sydney Power - 8x32-80100 8 32 - 80 100 120 140 AP - Sydney Power - 8x32-175100 8 32 - 175 100 124 144 AP - Sydney Pro-GPU - 4x16-100100 4 16 1 NVIDIA T4 100 100 441 461 AP - Sydney Max-GPU - 16x64-100100 16 64 1 NVIDIA T4 100 100 796 816 AP - Tokyo Lite - 2x8-8010 2 8 - 80 10 54 74 AP - Tokyo Lite - 2x8-8050 2 8 - 80 50 56 76 AP - Tokyo Lite - 2x8-80100 2 8 - 80 100 58 78 AP - Tokyo Lite - 2x8-175100 2 8 - 175 100 63 83 AP - Tokyo Standard - 4x16-8010 4 16 - 80 10 87 107 AP - Tokyo Standard - 4x16-8050 4 16 - 80 50 89 109 AP - Tokyo Standard - 4x16-80100 4 16 - 80 100 91 111 AP - Tokyo Standard - 4x16-175100 4 16 - 175 100 93 113 AP - Tokyo Power - 8x32-8010 8 32 - 80 10 122 142 AP - Tokyo Power - 8x32-8050 8 32 - 80 50 124 144 AP - Tokyo Power - 8x32-80100 8 32 - 80 100 128 148 AP - Tokyo Power - 8x32-175100 8 32 - 175 100 132 152 AP - Tokyo Pro-GPU - 4x16-100100 4 16 1 NVIDIA T4 100 100 473 493 AP - Tokyo Max-GPU - 16x64-100100 16 64 1 NVIDIA T4 100 100 828 848 EU - Frankfurt Lite - 2x8-8010 2 8 - 80 10 50 70 EU - Frankfurt Lite - 2x8-8050 2 8 - 80 50 52 72 EU - Frankfurt Lite - 2x8-80100 2 8 - 80 100 54 74 EU - Frankfurt Lite - 2x8-175100 2 8 - 175 100 58 78 EU - Frankfurt Standard - 4x16-8010 4 16 - 80 10 71 91 EU - Frankfurt Standard - 4x16-8050 4 16 - 80 50 73 93 EU - Frankfurt Standard - 4x16-80100 4 16 - 80 100 74 94 EU - Frankfurt Standard - 4x16-175100 4 16 - 175 100 77 97 EU - Frankfurt Power - 8x32-8010 8 32 - 80 10 114 134 EU - Frankfurt Power - 8x32-8050 8 32 - 80 50 116 136 EU - Frankfurt Power - 8x32-80100 8 32 - 80 100 119 139 EU - Frankfurt Power - 8x32-175100 8 32 - 175 100 124 144 EU - Frankfurt Pro-GPU - 4x16-100100 4 16 1 NVIDIA T4 100 100 432 452 EU - Frankfurt Max-GPU - 16x64-100100 16 64 1 NVIDIA T4 100 100 766 786 EU - Ireland Lite - 2x8-8010 2 8 - 80 10 47 67 EU - Ireland Lite - 2x8-8050 2 8 - 80 50 48 68 EU - Ireland Lite - 2x8-80100 2 8 - 80 100 51 71 EU - Ireland Lite - 2x8-175100 2 8 - 175 100 56 76 EU - Ireland Standard - 4x16-8010 4 16 - 80 10 64 84 EU - Ireland Standard - 4x16-8050 4 16 - 80 50 66 86 EU - Ireland Standard - 4x16-80100 4 16 - 80 100 67 87 EU - Ireland Standard - 4x16-175100 4 16 - 175 100 69 89 EU - Ireland Power - 8x32-8010 8 32 - 80 10 99 119 EU - Ireland Power - 8x32-8050 8 32 - 80 50 101 121 EU - Ireland Power - 8x32-80100 8 32 - 80 100 104 124 EU - Ireland Power - 8x32-175100 8 32 - 175 100 108 128 EU - Ireland Pro-GPU - 4x16-100100 4 16 1 NVIDIA T4 100 100 370 390 EU - Ireland Max-GPU - 16x64-100100 16 64 1 NVIDIA T4 100 100 649 669 EU - London Lite - 2x8-8010 2 8 - 80 10 58 78 EU - London Lite - 2x8-8050 2 8 - 80 50 60 80 EU - London Lite - 2x8-80100 2 8 - 80 100 62 82 EU - London Lite - 2x8-175100 2 8 - 175 100 68 88 EU - London Standard - 4x16-8010 4 16 - 80 10 78 98 EU - London Standard - 4x16-8050 4 16 - 80 50 80 100 EU - London Standard - 4x16-80100 4 16 - 80 100 84 104 EU - London Standard - 4x16-175100 4 16 - 175 100 89 109 EU - London Power - 8x32-8010 8 32 - 80 10 113 133 EU - London Power - 8x32-8050 8 32 - 80 50 117 137 EU - London Power - 8x32-80100 8 32 - 80 100 122 142 EU - London Power - 8x32-175100 8 32 - 175 100 129 149 EU - London Pro-GPU - 4x16-100100 4 16 1 NVIDIA T4 100 100 419 439 EU - London Max-GPU - 16x64-100100 16 64 1 NVIDIA T4 100 100 736 756 Israel - Tel Aviv Lite - 2x8-8010 2 8 - 80 10 44 64 Israel - Tel Aviv Lite - 2x8-8050 2 8 - 80 50 45 65 Israel - Tel Aviv Lite - 2x8-80100 2 8 - 80 100 48 68 Israel - Tel Aviv Lite - 2x8-175100 2 8 - 175 100 52 72 Israel - Tel Aviv Standard - 4x16-8010 4 16 - 80 10 60 80 Israel - Tel Aviv Standard - 4x16-8050 4 16 - 80 50 61 81 Israel - Tel Aviv Standard - 4x16-80100 4 16 - 80 100 62 82 Israel - Tel Aviv Standard - 4x16-175100 4 16 - 175 100 64 84 Israel - Tel Aviv Power - 8x32-8010 8 32 - 80 10 91 111 Israel - Tel Aviv Power - 8x32-8050 8 32 - 80 50 93 113 Israel - Tel Aviv Power - 8x32-80100 8 32 - 80 100 95 115 Israel - Tel Aviv Power - 8x32-175100 8 32 - 175 100 99 119 Israel - Tel Aviv Pro-GPU - 4x16-100100 4 16 1 NVIDIA T4 100 100 335 355 Israel - Tel Aviv Max-GPU - 16x64-100100 16 64 1 NVIDIA T4 100 100 586 606 SA - Sao Paulo Lite - 2x8-8010 2 8 - 80 10 68 88 SA - Sao Paulo Lite - 2x8-8050 2 8 - 80 50 69 89 SA - Sao Paulo Lite - 2x8-80100 2 8 - 80 100 72 92 SA - Sao Paulo Lite - 2x8-175100 2 8 - 175 100 79 99 SA - Sao Paulo Standard - 4x16-8010 4 16 - 80 10 102 122 SA - Sao Paulo Standard - 4x16-8050 4 16 - 80 50 104 124 SA - Sao Paulo Standard - 4x16-80100 4 16 - 80 100 108 128 SA - Sao Paulo Standard - 4x16-175100 4 16 - 175 100 113 133 SA - Sao Paulo Power - 8x32-8010 8 32 - 80 10 182 202 SA - Sao Paulo Power - 8x32-8050 8 32 - 80 50 187 207 SA - Sao Paulo Power - 8x32-80100 8 32 - 80 100 194 214 SA - Sao Paulo Power - 8x32-175100 8 32 - 175 100 204 224 SA - Sao Paulo Pro-GPU - 4x16-100100 4 16 1 NVIDIA T4 100 100 675 695 SA - Sao Paulo Max-GPU - 16x64-100100 16 64 1 NVIDIA T4 100 100 1195 1215 EU - Paris Lite - 2x8-8010 2 8 - 80 10 49 69 EU - Paris Lite - 2x8-8050 2 8 - 80 50 51 71 EU - Paris Lite - 2x8-80100 2 8 - 80 100 53 73 EU - Paris Lite - 2x8-175100 2 8 - 175 100 58 78 EU - Paris Standard - 4x16-8010 4 16 - 80 10 69 89 EU - Paris Standard - 4x16-8050 4 16 - 80 50 70 90 EU - Paris Standard - 4x16-80100 4 16 - 80 100 72 92 EU - Paris Standard - 4x16-175100 4 16 - 175 100 75 95 EU - Paris Power - 8x32-8010 8 32 - 80 10 N/A N/A EU - Paris Power - 8x32-8050 8 32 - 80 50 114 134 EU - Paris Power - 8x32-80100 8 32 - 80 100 118 138 EU - Paris Power - 8x32-175100 8 32 - 175 100 122 142 EU - Paris Pro-GPU - 4x16-100100 4 16 1 NVIDIA T4 100 100 426 446 EU - Paris Max-GPU - 16x64-100100 16 64 1 NVIDIA T4 100 100 749 769 IBM Cloud VPC Region Name vCPU Memory GPU Storage Volume (GB) Cloud PC Core - Flex Credit Price (Per VM Per Month) Cloud PC Complete - Flex Credit Price (Per VM Per Month) NA Dallas Lite - 2x10-100 2 10 - 100 54 74 NA Dallas Standard - 4x20-100 4 20 - 100 73 93 NA Dallas Power - 8x40-100 8 40 - 100 121 141 NA Dallas Pro-GPU - 16x80-100 16 80 1 NVIDIA L4 100 570 590 NA Dallas Max-GPU - 24x120-100 24 120 1 NVIDIA L40S 100 1181 1201 NA Dallas Add'l 10GB Storage Volume - - - 10 0.7 0.7 NA Montreal Lite - 2x10-100 2 10 - 100 56 76 NA Montreal Standard - 4x20-100 4 20 - 100 77 97 NA Montreal Power - 8x40-100 8 40 - 100 127 147 NA Montreal Add'l 10GB Storage Volume - - - 10 0.8 0.8 NA Toronto Lite - 2x10-100 2 10 - 100 56 76 NA Toronto Standard - 4x20-100 4 20 - 100 77 97 NA Toronto Power - 8x40-100 8 40 - 100 127 147 NA Toronto Pro-GPU - 16x80-100 16 80 1 NVIDIA L4 100 603 623 NA Toronto Max-GPU - 24x120-100 24 120 1 NVIDIA L40S 100 1251 1271 NA Toronto Add'l 10GB Storage Volume - - - 10 0.8 0.8 NA WDC Lite - 2x10-100 2 10 - 100 54 74 NA WDC Standard - 4x20-100 4 20 - 100 73 93 NA WDC Power - 8x40-100 8 40 - 100 121 141 NA WDC Pro-GPU - 16x80-100 16 80 1 NVIDIA L4 100 570 590 NA WDC Max-GPU - 24x120-100 24 120 1 NVIDIA L40S 100 1181 1201 NA WDC Add'l 10GB Storage Volume - - - 10 0.7 0.7 EU Frankfurt Lite - 2x10-100 2 10 - 100 55 75 EU Frankfurt Standard - 4x20-100 4 20 - 100 74 94 EU Frankfurt Power - 8x40-100 8 40 - 100 121 141 EU Frankfurt Pro-GPU - 16x80-100 16 80 1 NVIDIA L4 100 571 591 EU Frankfurt Max-GPU - 24x120-100 24 120 1 NVIDIA L40S 100 1182 1202 EU Frankfurt Add'l 10GB Storage Volume - - - 10 0.9 0.9 EU London Lite - 2x10-100 2 10 - 100 59 79 EU London Standard - 4x20-100 4 20 - 100 81 101 EU London Power - 8x40-100 8 40 - 100 134 154 EU London Pro-GPU - 16x80-100 16 80 1 NVIDIA L4 100 642 662 EU London Max-GPU - 24x120-100 24 120 1 NVIDIA L40S 100 1332 1352 EU London Add'l 10GB Storage Volume - - - 10 0.8 0.8 EU Madrid Lite - 2x10-100 2 10 - 100 60 80 EU Madrid Standard - 4x20-100 4 20 - 100 82 102 EU Madrid Power - 8x40-100 8 40 - 100 137 157 EU Madrid Pro-GPU - 16x80-100 16 80 1 NVIDIA L4 100 658 678 EU Madrid Max-GPU - 24x120-100 24 120 1 NVIDIA L40S 100 1367 1387 EU Madrid Add'l 10GB Storage Volume - - - 10 0.9 0.9 AP Osaka Lite - 2x10-100 2 10 - 100 59 79 AP Osaka Standard - 4x20-100 4 20 - 100 81 101 AP Osaka Power - 8x40-100 8 40 - 100 134 154 AP Osaka Pro-GPU - 16x80-100 16 80 1 NVIDIA L4 100 642 662 AP Osaka Max-GPU - 24x120-100 24 120 1 NVIDIA L40S 100 1332 1352 AP Osaka Add'l 10GB Storage Volume - - - 10 0.9 0.9 AP Sydney Lite - 2x10-100 2 10 - 100 61 81 AP Sydney Standard - 4x20-100 4 20 - 100 85 105 AP Sydney Power - 8x40-100 8 40 - 100 142 162 AP Sydney Pro-GPU - 16x80-100 16 80 1 NVIDIA L4 100 680 700 AP Sydney Max-GPU - 24x120-100 24 120 1 NVIDIA L40S 100 1414 1434 AP Sydney Add'l 10GB Storage Volume - - - 10 0.9 0.9 AP Tokyo Lite - 2x10-100 2 10 - 100 61 81 AP Tokyo Standard - 4x20-100 4 20 - 100 84 104 AP Tokyo Power - 8x40-100 8 40 - 100 141 161 AP Tokyo Pro-GPU - 16x80-100 16 80 1 NVIDIA L4 100 680 700 AP Tokyo Max-GPU - 24x120-100 24 120 1 NVIDIA L40S 100 1414 1434 AP Tokyo Add'l 10GB Storage Volume - - - 10 0.9 0.9 SA Sao Paulo Lite - 2x10-100 2 10 - 100 59 79 SA Sao Paulo Standard - 4x20-100 4 20 - 100 81 101 SA Sao Paulo Power - 8x40-100 8 40 - 100 134 154 SA Sao Paulo Pro-GPU - 16x80-100 16 80 1 NVIDIA L4 100 642 662 SA Sao Paulo Max-GPU - 24x120-100 24 120 1 NVIDIA L40S 100 1332 1352 SA Sao Paulo Add'l 10GB Storage Volume - - - 10 1 1 Add-On Products Flex Credit pricing for Cloud PC Add-On products is universal for all Cloud Providers and Regions.  Product Name Description Flex Credit Price Unit of Measure Private Network Access (HA Streaming Gateway Appliance)  Secure reverse proxy that enables users to access Cloud PCs without VPN. Supports Frame Remoting Protocol. 500 Per Pair Per Month Utility Server – Small  (2x8) Small Utility Server, with minimum of 2vCPU, and 8GB RAM Configuration may vary based on Cloud Provider. Storage may be purchased seperately.  125 Per VM Per Month Utility Server – Medium (4x16)  Medium Utility Server, with minimum of 4vCPU, and 16GB RAM. Configuration may vary based on Cloud Provider. Storage may be purchased seperately.  265 Per VM Per Month Utility Server – Large (8x32)  Large Utility Server, with minimum of 8vCPU, and 32GB RAM. Configuration may vary based on Cloud Provider. Storage may be purchased seperately.  525 Per VM Per Month Site To Site VPN Site To Site Virtual Private Network to connect your Cloud PCs to your applications and resources.  50 Per VPN Per Month Security Pulse  Vulnerability & Risk Monitoring for Cloud PCs 12 Per Cloud PC VM Per Month Microsoft OS License - Windows 11  Microsoft OS License - Windows 11  4 Per Cloud PC VM Per Month Directory Services (Azure AD, AD DS) Identity and access management for your Cloud PCs 2 Per User Per Month CrowdStrike Advanced Threat Protection  Machine learning, real-time threat intelligence, and endpoint detection and response (EDR) to detect and prevent malware and security breaches, including zero-day threats. 4 Per Cloud PC VM Per Month Dizzion Halo Halo is a "Secure Every Browser" platform that protects every browser session on any device. Gain real-time visibility, enforce zero-trust policies, and block advanced threats all without requiring users to switch browsers. 15 Per User Per Month Additional Network Transfer (Overage) Network Transfer, per GB, used in addition to the amount included per Cloud PC.  0.1 Per GB DaaS Flex Credit Rates Flex Credits offer a consumption-based pricing model that gives you full freedom to scale, resize, and reallocate desktops without modifying your contract. Choose from prepaid annual commit, monthly pay annual commit, or no-commit options.  To calculate estimated Flex Credits required, find the appropriate DaaS product, then multiply the Flex Credit price by the number of VMs or users. Repeat this step for each applicable Add-On product, then add the values together to get your total monthly Flex Credit budget. For prepaid annual commit, multiply by 12.  Example:  Standard per VM at 26 credits per VM per month for 50 VMs = 1,300 credits per month x 12 months = 15,600 credits annually Dizzion Halo at 15 credits per user per month for 100 users = 1,500 credits per month x 12 months = 18,000 credits annually 15,600 + 18,000 = 33,600 credits annually  Per  User Standard: 18 credits per user per month Education: 12 credits per user per month Per  VM Standard: 26 credits per VM per month Education: 16 credits per VM per month Add-On Products Product Name Description Flex Credit Price Unit of Measure Security Pulse  Vulnerability & Risk Monitoring for Cloud PCs 12 Per Cloud PC VM Per Month Microsoft OS License - Windows 11  Microsoft OS License - Windows 11  4 Per Cloud PC VM Per Month Directory Services (Azure AD, AD DS) Identity and access management for your users 2 Per User Per Month Dizzion Halo Halo is a "Secure Every Browser" platform that protects every browser session on any device. Gain real-time visibility, enforce zero-trust policies, and block advanced threats all without requiring users to switch browsers. 15 Per User Per Month