# GMO Cloud (Silver) — ClusterMAX GPU Cloud Review > GMO Cloud earns a ClusterMAX 2.0 Silver rating from SemiAnalysis. GMO Cloud, part of the sprawling Japanese conglomerate GMO Internet Group, presents a highly opinionated approach targeting their domestic market. The offering is built on a foundation of security that for us is so stringent it… - **Provider**: GMO Cloud - **ClusterMAX Tier**: Silver - **Tier definition**: Adequate offering with noticeable gaps compared to Gold or Platinum. Room for improvement. - **Authors**: Jordan Nanos, Daniel Nishball, Dylan Patel (SemiAnalysis) - **Published**: 2025-11-06 (Nov 06, 2025) - **Last updated**: 2025-11-06 (Nov 06, 2025) - **Source**: ClusterMAX 2.0 - **Canonical URL**: https://www.clustermax.ai/cloudreview/gmocloud - **Source article**: https://newsletter.semianalysis.com/p/clustermax-20-the-industry-standard - **Topics**: GMO Cloud review, GMO Cloud GPU cloud, GMO Cloud ClusterMAX rating, GMO Cloud Silver, Silver tier GPU cloud, GPU cloud review, neocloud review, Spectrum-X, Kubernetes, Slurm, NCCL, DCGM, ClusterMAX 2.0, SemiAnalysis --- GMO Cloud, part of the sprawling Japanese conglomerate GMO Internet Group, presents a highly opinionated approach targeting their domestic market. The offering is built on a foundation of security that for us is so stringent it alters the user experience, while still providing solid performance. We focused on slurm as kubernetes is not available, and quickly found that sinfo and scontrol are completely disabled for end-users. This decision, presumably made in the name of security, caused us issues with pre-baked scripts that depend on scontrol show hostnames $SLURM_JOB_NODELIST and other basic convenience functions. It also resulted in us having to modify some of our standard debugging practices, since users are unable to inspect the cluster state or topology. Thankfully, GMO provides a convenience command “snodes”, and a custom script, “get_master_addr.sh” which got us running jobs at expected performance. [](https://substackcdn.com/image/fetch/$s_!1YkV!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F47e14b4a-62b3-45c7-aee1-abea36895992_790x481.png)Source: SemiAnalysis using GMO convenience scripts In addition to these convenience scripts, a few other usability issues arose. GMO did not configure topology.conf, relying on a rationale that since they manually allocate customer clusters to servers that do not span across different Spectrum-X leaf switches, and organize everything by known hostnames, they are able to make topology awareness at the slurm level redundant. We think this points to a lack of experience running large customer clusters, and handling hardware failures in large multi-tenant environments. The theme of forcing non-standard workflows due to a focus on security continued with their containerization strategy. The environment lacks support for Pyxis and Enroot, effectively blocking teams that have standardized on Docker-based containers. Users are required to rebuild their entire workflow around Singularity, a relatively significant undertaking that creates another barrier to entry for new users. Unfortunately, this focus on security can also fall short at a basic level, creating a strange paradox. On one hand, simple command-line tools with no known exploits are locked down. On the other, we found outdated packages, such as nvidia-container-toolkit versions 1.16.2 and 1.17.4 on login and compute nodes respectively. While GMO acknowledges these are flagged by their internal vulnerability scanners and slated for an update, the presence of old software vulnerable to 9.0 Critical CVE’s running on our brand-new cluster contrasts sharply with the user-facing restrictions. Overall, GMO’s approach feels like security theater to us. On the positive side, the base environment is well-configured for HPC tasks. The nodes come pre-installed and configured with HPC-X, NCCL, and nvcc making it dead simple to build nccl-tests from source and run it at full expected bandwidth. We were also able to run torchtitan jobs at expected MFU. In addition, the standard dcgmi health -c program is configured properly as a Slurm HealthCheckProgram, addressing our background health check expectations. Finally, the platform lacks key observability and reliability features. There is no monitoring dashboard, though GMO states a Grafana-based solution is planned for a future release. For now, users must rely on basic Slurm email notifications for job status, and we could not identify any proactive health check system, placing the burden of failure detection largely on the user. Overall, GMO has established a clear advantage within Japan, especially with the region’s dependence on Slurm and other traditional HPC technologies. Support is strong, and we expect that example customers like Turing: and AI Robot Association (AIRoA) trust the offering as GMO Cloud is a leader domestically. We recommend that GMO focus on usability over security theatre, improve monitoring options for users via custom Grafana dashboard, improve passive and active health checks, and consider developing a kubernetes offering in the future. --- Other Silver tier providers: - Together: https://www.clustermax.ai/cloudreview/together - Lambda: https://www.clustermax.ai/cloudreview/lambda - Google Cloud (GCP): https://www.clustermax.ai/cloudreview/googlecloud - Amazon Web Services (AWS): https://www.clustermax.ai/cloudreview/amazonwebservices - Scaleway: https://www.clustermax.ai/cloudreview/scaleway - Cirrascale: https://www.clustermax.ai/cloudreview/cirrascale - GCORE: https://www.clustermax.ai/cloudreview/gcore - Firmus / Sustainable Metal Cloud (SMC): https://www.clustermax.ai/cloudreview/firmussustainablemetalcloud - Vultr: https://www.clustermax.ai/cloudreview/vultr - Voltage Park: https://www.clustermax.ai/cloudreview/voltagepark - Tensorwave: https://www.clustermax.ai/cloudreview/tensorwave Full ClusterMAX 2.0 + 2.1 index: https://www.clustermax.ai/cloudreview Full LLM dump of all reviews: https://www.clustermax.ai/llms-full.txt