Build the next model
Define the memory, data flow and connected GPU capacity your training run needs.
MODEL TRAININGFINE-TUNING
Explore requirements →AI & HIGH PERFORMANCE COMPUTING
Supercomputing.
On your terms.
From ambitious workloads to a clearer cloud plan. Understand the compute, connections and choices behind your next breakthrough.
TRAINING / INFERENCE / SIMULATION
START WITH THE WORK
Different questions.
Different compute.
Bring AI into production
Plan around response time, concurrency and the practical cost of serving a model.
INFERENCEAGENTIC AI
Explore requirements →Explore the possibilities
Frame demanding scientific and engineering problems before choosing a cluster.
SIMULATIONRESEARCH
Explore requirements →THE WHOLE SYSTEM MATTERS
More than a
GPU count.
Useful compute brings the right resources together. Look beyond the accelerator to the data, network and operating model around it.
Understand the infrastructure →01ComputeAccelerators, CPU and memory
02ConnectFabric, bandwidth and latency
03CoordinateScheduling, storage and resilience
04OperatePower, cooling and data location
THE COMPUTE PLANNER
Make the assumptions.
See the implications.
Compare two scenarios using your own GPU count, schedule, utilisation and hourly rate. Export a planning brief to take into a technical conversation.
Open the planner →ILLUSTRATIVE SCENARIO / 30 DAYS
64 GPUs × 24 hours × 30 days46,080
GPU-hours at US$2.50 per hourUS$115,200
Active-equivalent hours at 70%32,256
User-editable example. Compute rental only; excludes storage, networking, tax and other charges. Not a provider quote.RESEARCH & PERSPECTIVE
Read the evidence.
Ask better questions.
Oracle broadens its accelerator roadmap
Oracle announced Google TPUs on OCI for 2027. Future availability remains subject to rollout.
Read the context →AI cloud extends across the workload lifecycle
Nebius’s Q2 shareholder letter describes its integrated approach to training and inference.
Read the context →GPU clusters need a connected fabric
Vultr documentation distinguishes compute, bare metal and GPU fabric clusters.
Read the context →AN INTERCONNECTED ECOSYSTEM
Know who does what.
Discover the roles of cloud providers, hardware platforms and orchestration software. Follow the original sources to assess fit for your own workload.
Explore the ecosystem →Capacity is one part of the decision.
Evaluate data location, software compatibility, support responsibilities and a practical exit plan alongside cost and performance.
Compare deployment models →Independent information and planning concept. Companies mentioned are research references, with no partnership or endorsement implied.
CLARITY BEFORE CAPACITY
Bring a better brief
to the conversation.
Use the planner to organise your requirements, then explore the infrastructure questions that matter to your project.