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Complete stack
NVIDIA for the AI runtime, FusioNative for the cloud around it.
Compare
FusioNative vs the NVIDIA AI stack
NVIDIA's software stack covers the AI factory on NVIDIA hardware: AI Enterprise and NIM for supported models and runtimes, Run:ai (open source since October 2026) and the KAI Scheduler for GPU scheduling, Base Command Manager for cluster bring-up and Mission Control for operating Blackwell and Rubin systems. FusioNative is a vendor-neutral cloud layer: tenancy, self-service, metering and chargeback, VMs, storage and networking across NVIDIA and AMD estates.
Last updated · Fusionative
Category frame
NVIDIA · AI factory software (AI Enterprise, NIM, Run:ai, Base Command Manager, Mission Control)
NVIDIA's stack is the reference for running NVIDIA AI factories. Its multi-tenant documentation leaves tenant provisioning, infrastructure isolation and billing to the operator. FusioNative provides that layer and works alongside NVIDIA software such as NIM.
Ownership split
Own the depth. Own the cloud.
They own infrastructure depth. You own the cloud operating model. Use this frame in evaluations, not feature-by-feature checklists.
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NVIDIA AI Enterprise, Run:ai and Mission Control typically owns
- Deepest integration with NVIDIA GPUs, networking and systems
- NIM optimized inference microservices and the NVIDIA model catalog
- Run:ai and KAI Scheduler for GPU scheduling, fair share and fractions
- Base Command Manager and Mission Control for cluster and AI factory operations
- Validated reference architectures with OEMs
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FusioNative typically owns
- Multi-tenant cloud operations and economics
- Mixed-vendor accelerators and VMs
- Integrated storage, networking, security and observability
Detailed comparison
NVIDIA AI Enterprise, Run:ai and Mission Control and FusioNative, side by side.
Category and operating-model differences. Use this table in evaluations instead of checkbox spam.
| Dimension | NVIDIA AI Enterprise, Run:ai and Mission Control | FusioNative |
|---|---|---|
| Primary job | Run AI workloads well on NVIDIA infrastructure. | Operate the estate as a multi-tenant cloud. |
| Tenancy | Run:ai multi-tenant mode: dedicated clusters for untrusted tenants; isolation and provisioning left to the host. | Organizations, projects and isolation managed by the platform. |
| Billing | Quotas and usage reports; no billing or chargeback described. | GPU-model rate cards and monthly invoices per tenant. |
| Accelerators | NVIDIA. | NVIDIA and AMD. |
| Licensing (public) | AI Enterprise per GPU (list from $4,500 per GPU per year); Run:ai open source. | Editions; pricing on request. |
Decision guide
When to choose whom.
Honest selection criteria. The right answer is often layered coexistence.
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Choose NVIDIA AI Enterprise, Run:ai and Mission Control when
- You run NVIDIA DGX or NVL72 systems and want NVIDIA's supported operations stack end to end.
- You need scheduling for internal research teams, not a multi-tenant cloud.
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Choose FusioNative when
- You sell or share GPU capacity to many tenants and need billing.
- You run mixed NVIDIA and AMD accelerators or many VMs.
Differentiators
Where FusioNative is usually evaluated
Commercial and architectural axes, not a checkbox war.
evaluation axes
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Tenant onboarding
Tenant onboarding, self-service catalog, metering and chargeback
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NVIDIA and AMD accelerators on one platform
NVIDIA and AMD accelerators on one platform
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KubeVirt VMs
KubeVirt VMs, Ceph and Cilium integrated
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Vendor-neutral
Vendor-neutral, self-hosted control plane
Architecture
Coexistence, not false replacement.
Most estates use both: NVIDIA drivers, NIM and possibly Run:ai inside tenant clusters, with FusioNative as the cloud layer for tenants, catalog and metering.
- NVIDIA's software is strongest from the hardware up to the AI runtime.
- FusioNative is strongest at tenancy, self-service and economics across the estate.
Buyer outcomes
What a good evaluation produces.
NVIDIA's software runs AI on NVIDIA hardware; FusioNative runs the multi-tenant cloud around it. They are complementary for providers and shared estates.
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Vendor neutrality
One cloud layer across accelerator vendors.
Ask in the room
Evaluation questions that keep the category honest.
Use these in RFPs, architecture reviews, and executive briefings.
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Q1
Who provisions and isolates tenants in our design?
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Q2
Where does metering turn into an invoice or a chargeback?
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Q3
Do we need non-NVIDIA accelerators or VMs on the same platform?
FAQ
Frequently asked questions
Does FusioNative replace NVIDIA AI Enterprise?
No. It runs alongside NVIDIA software, can serve NVIDIA NIM models, and adds the multi-tenant cloud layer: tenants, catalog, metering and chargeback.
Is Run:ai still needed?
Run:ai or the KAI Scheduler can keep scheduling GPU jobs inside tenant clusters. FusioNative manages tenants and economics across the estate.
How much does NVIDIA AI Enterprise cost?
NVIDIA's licensing guide lists suggested self-managed prices per GPU, starting at $4,500 per GPU per year; partners set final prices.
Next step
Bring this framing into a live architecture review.
Book a demo with your estate context, or return to the compare hub for the other stacks.