[Yandex Cloud documentation](../../../index.md) > [Yandex StoreDoc](../../index.md) > [Concepts](../index.md) > Host classes > Archive > Before June 20, 2023 # Yandex StoreDoc host classes before June 20, 2023 The host class determines the computing power allocated for each host in a cluster. When you change the host class for a cluster, all existing hosts change accordingly. The host class determines the available [disk types](../storage.md): * **s1**, **s2**, **m2**: `network-ssd`, `network-hdd`, `local-ssd`, `network-ssd-nonreplicated`. * **c3**, **s3**, **m3**: `network-ssd`, `network-hdd`, `network-ssd-nonreplicated`. * **b1**, **b2**, **b3**: `network-ssd`, `network-hdd`. For storage size limitations, see [Quotas and limits](../limits.md). ## Available host classes {#available-flavors} Hosts in Yandex StoreDoc clusters are deployed on Yandex Compute Cloud VMs. You can create these VMs on any platforms Compute Cloud supports. To learn more about the platforms, see [Platforms](../../../compute/concepts/vm-platforms.md). The full list of possible host configurations on each platform is provided below. Configuration types: * **s1**, **s2**, **s3**: Standard configurations with 4:1 RAM GB to vCPU ratio. * **m2**, **m3**: Configurations with an increased RAM GB to vCPU ratio (8:1). These configurations may be useful for clusters with higher cache requirements. * **c3**: Configurations with a reduced RAM GB to vCPU ratio (2:1). These configurations may be useful for clusters with higher processor performance requirements. * **b1**, **b2**, **b3**: Configurations with a guaranteed vCPU share under 100%. This host class is intended for test load, while the minimum recommended host configuration for production solutions is two vCPUs with a guaranteed share of 50%. {% note info %} Hosts with a guaranteed vCPU share under 50% cannot be used in multi-host clusters. {% endnote %} | Host class name | Number of CPUs | CPU performance | RAM, GB | Disk
size, GB | |-------------------|----------------|------------------------|---------|----------------------| | **Intel Broadwell** | | b1.nano | 2 | 5% | 2 | 10 - 25 | | b1.micro | 2 | 20% | 2 | 10 - 50 | | b1.medium | 2 | 50% | 4 | 10 - 512 | | s1.micro | 2 | 100% | 8 | 10 - 2232 | | s1.small | 4 | 100% | 16 | 10 - 2232 | | s1.medium | 8 | 100% | 32 | 10 - 2232 | | s1.large | 16 | 100% | 64 | 10 - 2232 | | s1.xlarge | 32 | 100% | 128 | 10 - 2232 | | **Intel Cascade Lake** | | b2.nano | 2 | 5% | 2 | 10 - 25 | | b2.micro | 2 | 20% | 2 | 10 - 50 | | b2.medium | 2 | 50% | 4 | 10 - 512 | | m2.micro | 2 | 100% | 16 | 10 - 2232 | | m2.small | 4 | 100% | 32 | 10 - 2232 | | m2.medium | 6 | 100% | 48 | 10 - 2232 | | m2.large | 8 | 100% | 64 | 10 - 2232 | | m2.xlarge | 12 | 100% | 96 | 10 - 2232 | | m2.2xlarge | 16 | 100% | 128 | 10 - 2232 | | m2.3xlarge | 24 | 100% | 192 | 10 - 2232 | | m2.4xlarge | 32 | 100% | 256 | 10 - 2232 | | m2.5xlarge | 40 | 100% | 320 | 10 - 2232 | | m2.6xlarge | 48 | 100% | 384 | 10 - 2232 | | m2.7xlarge | 56 | 100% | 448 | 10 - 2232 | | m2.8xlarge | 64 | 100% | 512 | 10 - 2232 | | s2.micro | 2 | 100% | 8 | 10 - 2232 | | s2.small | 4 | 100% | 16 | 10 - 2232 | | s2.medium | 8 | 100% | 32 | 10 - 2232 | | s2.large | 12 | 100% | 48 | 10 - 2232 | | s2.xlarge | 16 | 100% | 64 | 10 - 2232 | | s2.2xlarge | 24 | 100% | 96 | 10 - 2232 | | s2.3xlarge | 32 | 100% | 128 | 10 - 2232 | | s2.4xlarge | 40 | 100% | 160 | 10 - 2232 | | s2.5xlarge | 48 | 100% | 192 | 10 - 2232 | | s2.6xlarge | 64 | 100% | 256 | 10 - 2232 | | **Intel Ice Lake** | | b3-c1-m4 | 2 | 50% | 4 | 10 - 512 | | s3-c2-m8 | 2 | 100% | 8 | 10 - 2232 | | s3-c4-m16 | 4 | 100% | 16 | 10 - 2232 | | s3-c8-m32 | 8 | 100% | 32 | 10 - 2232 | | s3-c12-m48 | 12 | 100% | 48 | 10 - 2232 | | s3-c16-m64 | 16 | 100% | 64 | 10 - 2232 | | s3-c24-m96 | 24 | 100% | 96 | 10 - 2232 | | s3-c32-m128 | 32 | 100% | 128 | 10 - 2232 | | s3-c40-m160 | 40 | 100% | 160 | 10 - 2232 | | s3-c48-m192 | 48 | 100% | 192 | 10 - 2232 | | s3-c64-m256 | 64 | 100% | 256 | 10 - 2232 | | s3-c80-m320 | 80 | 100% | 320 | 10 - 2232 | | s3-c96-m576 | 96 | 100% | 576 | 10 - 2232 | | m3-c2-m16 | 2 | 100% | 16 | 10 - 2232 | | m3-c4-m32 | 4 | 100% | 32 | 10 - 2232 | | m3-c6-m48 | 6 | 100% | 48 | 10 - 2232 | | m3-c8-m64 | 8 | 100% | 64 | 10 - 2232 | | m3-c12-m96 | 12 | 100% | 96 | 10 - 2232 | | m3-c16-m128 | 16 | 100% | 128 | 10 - 2232 | | m3-c24-m192 | 24 | 100% | 192 | 10 - 2232 | | m3-c32-m256 | 32 | 100% | 256 | 10 - 2232 | | m3-c40-m320 | 40 | 100% | 320 | 10 - 2232 | | m3-c48-m384 | 48 | 100% | 384 | 10 - 2232 | | m3-c56-m448 | 56 | 100% | 448 | 10 - 2232 | | m3-c64-m512 | 64 | 100% | 512 | 10 - 2232 | | m3-c80-m640 | 80 | 100% | 640 | 10 - 2232 | | c3-c2-m4 | 2 | 100% | 4 | 10 - 2232 | | c3-c4-m8 | 4 | 100% | 8 | 10 - 2232 | | c3-c8-m16 | 8 | 100% | 16 | 10 - 2232 | | c3-c12-m24 | 12 | 100% | 24 | 10 - 2232 | | c3-c16-m32 | 16 | 100% | 32 | 10 - 2232 | | c3-c24-m48 | 24 | 100% | 48 | 10 - 2232 | | c3-c32-m64 | 32 | 100% | 64 | 10 - 2232 | | c3-c40-m80 | 40 | 100% | 80 | 10 - 2232 | | c3-c48-m96 | 48 | 100% | 96 | 10 - 2232 | | c3-c64-m128 | 64 | 100% | 128 | 10 - 2232 | | c3-c80-m160 | 80 | 100% | 160 | 10 - 2232 | | c3-c96-m192 | 96 | 100% | 192 | 10 - 2232 |