Most GPU operators spend the first 6 months just wiring up scheduling, multi-tenancy, and billing. GPUForge replaces that entire layer — so you can focus on the work that actually takes years.
Every team starts from the same place: raw GPU hardware. And every team hits the same wall — scheduling, multi-tenancy, and billing aren't solved problems you can pull off a shelf. Teams custom-build it from scratch. Many never make it past this phase.
One deployable platform that replaces the entire orchestration layer — scheduling, multi-tenancy, metering, billing, and cost optimization.
Topology-aware scheduling across SLURM and Kubernetes. Fractional GPU sharing. Gang scheduling for distributed training. Priority queues per tenant.
Namespace-level GPU quotas with hard enforcement. Network isolation. Resource guarantees. Serve multiple customers on shared infrastructure safely.
Per-second GPU metering with full audit trail. Real-time utilization dashboards. Cost attribution per tenant, per job, per GPU type.
SKU management, usage-based invoicing, and billing APIs. Turn your cluster into a revenue-generating service without building a billing system.
Unified control plane across on-premises and cloud GPUs. Burst to cloud when on-prem is saturated. Unified cost view across both.
Automatic detection of unmeasured GPU usage, quota overruns, and billing gaps. Stop leaving money on the table from ungated compute access.
Three deployment models — one platform. Match the right infrastructure tier to every workload, from dedicated enterprise tenants to sub-second MIG slices.
GPU servers plus Notebook Pod service deployed as Kubernetes workloads — CUDA/cuDNN pre-configured, ready for data science and ML teams who want a compute environment, not infrastructure headaches.
Full GPU VM instances and serverless MIG (Multi-Instance GPU) slices in the same platform. Tenants pick the granularity — from a full A100 to a 10GB MIG slice — and pay only for what runs.
The alternatives are either locked into a vendor ecosystem, built for a different use case, or unsupported open source. GPUForge is purpose-built for operators who need to run multi-tenant AI infrastructure profitably.
| Platform | Vendor-neutral | Multi-tenancy | Built-in billing | Hybrid on-prem+cloud | Commercial support | Pricing |
|---|---|---|---|---|---|---|
| GPUForge | ✓ | ✓ | ✓ | ✓ | ✓ | From $2K/mo |
| Run:ai | ✗ NVIDIA-owned | ✓ | ✗ | ~ | ✓ | $$$ |
| Rafay | ✓ | ✓ | ✗ | ✓ | ✓ | $$$ |
| dstack | ✓ | ~ | ✗ | ✓ | ✗ OSS only | Free (DIY) |
| SkyPilot | ✓ | ✗ | ✗ | ~ | ✗ OSS only | Free (DIY) |
If you own or manage GPU clusters and need to monetize them — whether that's external customers or internal teams — GPUForge is the platform.
You have the hardware and the data center. GPUForge adds the orchestration and billing layer so you can sell GPU compute as a service without building it yourself.
Internal GPU clusters serving multiple teams or business units. GPUForge enforces quotas, tracks cost attribution, and stops the fights over who's using the GPUs.
Universities and labs running GPU clusters across departments. Multi-tenant scheduling with fair-share policies. Usage reporting for grant compliance.
National and regional programs building domestic AI infrastructure. Vendor-neutral, on-premises, fully auditable. No dependency on foreign cloud providers.
No per-feature modules. No sales engineering required. One platform price that scales with the GPUs you manage.
Designed for GPU operators managing 10 to 2,000+ GPUs. Get a deployment timeline, pricing, and a technical walkthrough — no commitment required.
No spam. No sales calls. You'll hear from the founder directly.
We'll review your cluster setup and reach out within 24 hours with a deployment timeline and pricing outline.