GMI Cloud Supports NVIDIA Dynamo 1.0 and OpenShell as Launch Partner

GMI Cloud is part of the initial cohort of cloud providers working with NVIDIA Dynamo, their production-grade, open-source inference platform. Our AI stack also supports NVIDIA OpenShell runtime, helping extend this foundation from high-performance inference orchestration to the runtime layer needed for long-running autonomous agents.

Here's what that means, and why the infrastructure we've built makes us a natural fit.

What NVIDIA Dynamo 1.0 Does

NVIDIA Dynamo is the distributed inference framework designed to orchestrate GPU clusters for production-scale AI workloads. Think of it as the coordination layer that makes a cluster of GPUs behave as a coherent inference system rather than a collection of independent machines: KV-cache-aware request routing, GPU resource planning, disaggregated prefill and decode, and intelligent memory management across the full hardware hierarchy.

Used together with NVIDIA GB300 NVL72, NVIDIA Dynamo delivers up to 50x higher throughput per megawatt and 35x lower cost per token compared to the Hopper platform, per independent SemiAnalysis InferenceX benchmarks. For teams running large reasoning models or multi-step agentic pipelines those numbers translate directly into product quality and infrastructure cost.

For technical teams, the specifics that matter: NVIDIA Dynamo's KV-cache-aware router eliminates redundant computation by directing requests to GPUs that already hold relevant context. The GPU Resource Planner dynamically rebalances prefill and decode capacity as load shifts in real time. Disaggregated serving allows prefill and decode to be independently scaled, which is how you maintain predictable latency under long-context, high-concurrency workloads.

That matters even more as AI systems move beyond one-shot responses toward persistent, multi-step agents. In that architecture, NVIDIA Dynamo helps optimize the inference backbone, while NVIDIA OpenShell runtime help govern how those agents execute over time.

GMI Cloud and NVIDIA are also collaborating on NVIDIA NemoClaw, an open-source stack designed to simplify the deployment of OpenClaw always-on assistants with a single command. As a core component of the NVIDIA Agent Toolkit, it integrates the NVIDIA OpenShell runtime, a secure environment for autonomous agents, and supports open-source models like NVIDIA Nemotron.

Why GMI Cloud Is a Natural Fit for This Platform

GMI Cloud has been building toward this kind of infrastructure for some time. We're a full-stack AI infrastructure provider with owned data centers, owned networking, owned orchestration, and an Inference Engine built specifically for production AI workloads rather than general-purpose compute adapted for them.

That foundation is part of why GMI Cloud became one of NVIDIA's Reference Platform Cloud Partners, one of seven cloud providers globally to earn that designation. The program validates that a provider's cluster architecture, networking, and inference stack meet NVIDIA's standards for demanding AI workloads. It also gave us access to NVIDIA Blackwell and the engineering alignment to deploy it correctly. That engineering alignment matters not only for high-performance inference frameworks like NVIDIA Dynamo, but also for adjacent agent development tools such as NVIDIA OpenShell, where runtime safety and execution control become increasingly important as workloads grow more autonomous.

NVIDIA Dynamo is designed to run on exactly this kind of infrastructure: disaggregated, memory-hierarchy-aware, orchestrated at the cluster level. Being part of the launch cohort reflects the alignment between what NVIDIA Dynamo requires and what GMI Cloud has built.

What This Means for Teams Evaluating Infrastructure

For technical leaders choosing where to run production inference, NVIDIA Dynamo is designed for providers with the hardware depth and software integration to run it well. GMI Cloud's inclusion in the launch cohort, alongside our NVIDIA Reference Platform Cloud Partner status, reflects that our infrastructure meets that bar. And as teams move toward long-running, tool-using agents, support for technologies like NVIDIA OpenShell will matter alongside raw inference performance.

For business leaders evaluating AI infrastructure spend: the cost and throughput improvements NVIDIA Dynamo enables — 35x lower cost per token, 50x higher throughput per megawatt versus the prior generation — are only accessible on infrastructure built to support them. The question worth asking your current provider is whether their stack is positioned to deliver those gains, or whether they're still catching up to the hardware requirements.

GMI Cloud is built for this. NVIDIA Dynamo reflects the strength of the inference infrastructure we've built, and support for NVIDIA NemoClaw points to where that stack is going next: toward safer, more persistent, and more production-ready autonomous systems.

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