AI training
& fine-tuning
Match model size and training goals to GPU memory, interconnects, and the time you have to finish.
Memory · Cluster scale · ThroughputGPU AS A SERVICE. HUMAN ADVICE.
Ambitious workloads.
The right GPU cloud.
From your first AI model to production at scale, find GPU infrastructure that fits your workload, budget, and next move.
30 minutes. Your requirements. No cost for our advisory services.
COMPUTE WITH CONFIDENCE01 / GPU CLOUD
BUILT AROUND YOUR WORKLOAD
More than a GPU.
The right environment.
An advisor on your side.
From requirements to provider selection.
Workload fitCost clarityProvider choice
Specialized guidance.
A connected advisory portfolio.
01 / START WITH THE WORKLOAD
What are you
building next?
The best GPU cloud starts with what you need to run. We help translate your goals into infrastructure requirements providers can actually quote.
AI training
Production AI
& inference
Plan for response time, concurrent requests, and dependable serving as usage grows.
Latency · Concurrency · ScalingRendering
& visualization
Source compute for rendering, 3D workloads, and graphics applications without buying for every peak.
Software fit · Burst capacity · I/OResearch
& simulation
Align GPU architecture and precision with scientific computing, simulation, and batch jobs.
Precision · Job duration · Data flowStill defining the project? That’s a good time to talk.
Work through it with an advisor03 / EXPLORE THE PROVIDER LANDSCAPE
Meet the GPU
cloud specialists.
Neoclouds specialize in GPU and AI infrastructure. Explore providers such as Edgevana and the platforms below, then work with an advisor to build a shortlist around your workload, region, and budget.
Dedicated GPU infrastructure
Edgevana
GPU-as-a-service and dedicated AI clusters, with bare-metal, Kubernetes, and Slurm deployment options for training and inference.
What to discussDeployment location, hardware control, and cluster requirements.
Discuss EdgevanaAI cloud at cluster scale
CoreWeave
A GPU cloud built around a Kubernetes-native environment, with compute, storage, networking, and managed services for AI workloads.
What to discussCluster scale, storage performance, and operational support.
Discuss CoreWeaveAI infrastructure & managed services
Nebius
An AI cloud spanning GPU infrastructure, developer tooling, and managed inference for teams moving from experimentation to production.
What to discussTraining and inference needs, tooling, and deployment regions.
Discuss NebiusGPU instances & clusters
Lambda
GPU instances, 1-Click Clusters, and dedicated Superclusters for AI development, distributed training, and inference.
What to discussInstance versus cluster needs, orchestration, and capacity planning.
Discuss LambdaAI cloud & managed orchestration
Crusoe
GPU compute with accelerated storage and networking, plus managed Kubernetes and Slurm options for AI infrastructure.
What to discussNetworking, orchestration, and ongoing infrastructure operations.
Discuss CrusoeGPU development & serverless inference
Runpod
GPU Pods, autoscaling Serverless endpoints, and multi-GPU Clusters for development, training, and production inference.
What to discussPersistent versus serverless compute, scaling, and workload patterns.
Discuss RunpodA starting point for your evaluation, not a provider ranking. Provider names link to their official websites. We confirm current offerings, availability, and commercial fit as part of your shortlist. Compare published pricing →
04 / PUT PRICING IN CONTEXT
Published GPU rates.
A clearer starting point.
Use these H100 examples to start your budget conversation. GPU count, included resources, deployment region, and purchasing terms all affect what you actually pay.
USD · Published rate examplesChecked
Scroll the table horizontally to see billing details and source links.
| Provider | Example configuration | Published price | How to read the rate | Official source |
|---|---|---|---|---|
| Edgevana | H100 SXM · 80 GBGPU marketplace listing | From $1.99per GPU / hour | The selected multi-GPU listing shows $7.98/hour total. The per-GPU figure is not the full server charge; listings vary by configuration. | View pricing |
| CoreWeave | 8 × HGX H100 · 80 GB eachOn-demand instance | $49.24per 8-GPU instance / hour | Approximately $6.16 per GPU-hour, calculated by dividing the instance rate by eight. The quoted unit is the full instance. | View pricing |
| Nebius | HGX H100On-demand GPU instance | $3.85per GPU / hour | Published with 16 vCPUs and 200 GB RAM per GPU. Preemptible pricing is a separate rate with different interruption terms. | View pricing |
| Lambda | 1 × H100 SXM · 80 GBOn-demand instance | $4.29per GPU / hour | The single-GPU configuration includes 26 vCPUs, 225 GiB RAM, and 2.75 TiB SSD. Multi-GPU configurations have different per-GPU rates. Taxes are additional. | View pricing |
| Crusoe | H100 HGX · 80 GBOn-demand GPU instance | $3.90per GPU / hour | Multiply by the instance’s GPU count. This is the compute rate; storage and managed services have separate pricing. | View pricing |
| Runpod | H100 SXM · 80 GBGPU Pod listing | $3.49per GPU / hour | The listed configuration has 20 vCPUs and 125 GB RAM. Storage, Serverless endpoints, and Clusters are priced separately. | View pricing |
A dated snapshot of published prices, not a live quote or an equivalent-performance comparison. Rates and availability can change. Confirm region, GPU count, storage, data transfer, support, taxes, and minimum commitments before budgeting. Spot, preemptible, reserved, and serverless rates are separate purchasing models.
Compare your total cost with an advisor.
Bring your workload or an existing quote. We’ll help you compare configurations, expected usage, and provider terms. Our advisory services cost you nothing; we’re compensated by whichever provider you choose through us.
LOOK BEYOND THE HOURLY RATE
A faster GPU isn’t always
a better business decision.
Compare the cost of completing your workload, with the performance and support you need. We help put competing proposals on the same basis.
01
Compute that fitsMemory, GPU count, interconnects, and measured workload performance.
02
The complete costCompute, storage, data transfer, software, support, and idle capacity.
03
Terms you can operate withCapacity assurance, service commitments, security requirements, and exit options.
05 / A CLEARER WAY FORWARD
Expert guidance.
Grounded in your requirements.
You bring the project. We help make the infrastructure decision manageable, from the first conversation to comparing provider proposals.
- 01
Define what matters.
Talk through your workload, current environment, budget, location, and timeline. You don’t need every specification figured out.
- 02
Build a practical shortlist.
Identify deployment models and providers worth evaluating. Check workload fit, operating responsibilities, and capacity with the providers.
- 03
Compare. Validate. Decide.
Review proposals, clarify the full cost, and define any benchmark or proof of concept needed before you commit.
Advice with a wider view. GPU Cloud Advisors is operated by Foretel Solutions, Inc., an authorized Bridgepointe Technologies partner. Our advisory services are provided at no cost to you. We’re compensated by whichever provider you choose through us. Your provider’s infrastructure charges and contract terms are separate.
LET’S FIND YOUR WAY FORWARD
Your next move
starts with a conversation.
Meet with an advisor to discuss your GPU requirements, explore realistic options, and agree on the next step for your project.
Our advisory services are free to you. We’re compensated by whichever provider you choose through us.
YOUR GPU CLOUD CONSULTATIONBring your questions.
Bring your questions.
We’ll bring perspective.
A few details help us make the most of your time:
- What you’re building or running
- Your GPU or memory needs, if known
- Target location and launch timeline
- Budget range or an existing proposal
Book securely on Calendly. Times appear in your time zone.
Prefer to call? 844-506-2299
What is GPU as a service?
GPU as a service gives you access to GPU compute through a provider instead of purchasing and hosting the hardware yourself. Services range from virtual machines and dedicated clusters to managed AI platforms. Billing, control, capacity commitments, and support vary by provider.
Can you help if we don’t know which GPU we need?
Yes. Start with the workload: model or application, data size, response-time needs, and expected usage. We’ll help turn that into a set of requirements and identify where benchmarking is needed. GPU memory, software compatibility, and the surrounding infrastructure matter alongside the GPU model.
Do you sell GPU capacity directly?
We’re an advisory resource. We help you evaluate options and connect with providers for proposals. The provider confirms capacity, pricing, technical suitability, and contract terms. This website is not a live inventory or instant quoting service.
How much do your advisory services cost?
There is no cost to you for our advisory services, and no obligation to choose a provider. We’re compensated by whichever provider you select through us. You pay your chosen provider for the infrastructure and services you purchase under your agreement with them.
Can you review a quote we already have?
Yes. Bring the proposal and any workload assumptions behind it. We can help identify missing costs, clarify capacity commitments and support, and determine which alternatives deserve a closer look.
Can we compare GPU cloud with owning our hardware?
Yes. We can discuss the tradeoffs between renting compute and owning GPUs, including utilization, staffing, power, cooling, connectivity, and refresh cycles. For facility requirements, our Colocation Scout GPU guide is a useful starting point.
How we frame the technical comparison
Our comparison focuses on workload requirements rather than a universal provider ranking. Useful primary references include NVIDIA’s model and memory guidance, AWS accelerated computing specifications, AWS purchasing options, and cloud pricing fundamentals. These examples inform the evaluation criteria; they are not a complete provider list or an endorsement. Verify current features, availability, and terms with the provider.