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Beirit Harvey

TensorWave earns Silver in SemiAnalysis ClusterMAX: reliable AMD GPU access, open-source flexibility, and lower TCO so builders can iterate and ship faster.

Our ClusterMAX™ Rank Confirms the AI Cloud We’ve Been Building

Big news: TensorWave has been awarded a Silver rating in the SemiAnalysis ClusterMAX rankings, underscoring our progress and commitment to accessible, high-performance AMD compute. If you’re a builder, one thing matters most: can you get reliable access to modern GPUs and iterate fast? That’s why the recent spotlight on TensorWave is interesting, because buried inside the benchmarks and metrics are clear positives that directly benefit engineering teams.

The team at Seminanalysis notes, “... The TensorWave team is always very responsive to our feedback and quick to address issues we raise. We have also seen a general trend of reliability improving over time.”

TensorWave earned a Silver rating after upgrading our platform with fully managed Slurm and managed Kubernetes, exactly the capabilities ClusterMAX emphasizes. The framework explicitly prioritizes out-of-the-box Slurm/Kubernetes and scores providers across security, reliability, networking, storage, and monitoring; our rollout of production-ready schedulers, cluster-level health checks, and faster ‘time-to-value’ on AMD Instinct™ fleets mapped directly to those criteria and lifted our ranking.

Additionally, and perhaps more importantly, we added ISO/IEC 27001 certification, reinforcing the security our customers rely on.


A Focused Bet On AMD (And Real Scale)

TensorWave has made an explicit, company-level commitment to AMD, backed by a significant raise and a large MI325X footprint in Tucson. For builders, that kind of focus translates to practical upsides:

 * Capacity you can actually use. A dedicated AMD provider means you’re likely to find quota on high-memory MI3xx-class GPUs when you need it, rather than waiting in line behind generic, mixed-fleet pools.
 * Avoid the GPU vendor lock-in. By leaning on open-source tools and standards, you’re not tied to one GPU brand. It’s easier to move your work where capacity is available, keep leverage on prices, and stay flexible as your needs grow.
 * More memory for bigger jobs. With extra on-GPU memory, you can fit longer inputs and more work into each run, so you get higher throughput and fewer hassles.


What This Means for Builders

If you’re evaluating where to place your next training run, finetune, or inference service:

 1. AMD-first clouds are becoming a real, durable option. With serious MI325X capacity and an AMD-exclusive focus, you can plan for larger context, higher batch efficiency, and better consolidation, often at a lower TCO envelope.
 2. Choose partners that iterate with you. Fast response to developer feedback, measurable reliability gains, and openness to tune Slurm/K8s plumbing are practical signals you’ll feel in time-to-run, not just in a sales deck.


The Takeaway

Access + iteration beats static checklists. A provider willing to ship fixes quickly, invest deeply in AMD-specific telemetry, and open doors for benchmarking is the kind of platform that helps teams ship more experiments and graduate winners to production sooner!


About TensorWave

TensorWave is the AI neocloud purpose-built for performance. Powered exclusively by AMD Instinct™ Series GPUs, we deliver high-bandwidth, memory-optimized infrastructure that scales with your most demanding models—training or inference.

Ready to get started? Connect with a Sales Engineer.

Our ClusterMAX™ Rank Confirms the AI Cloud We’ve Been Building

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