Inference
Distribute model execution across GPUs. Access leading models through one familiar API.
Explore inference
Access leading models through one OpenAI-compatible API. Compare inference prices, choose your model, and start building.
Match price, memory and connectivity to the work. Then coordinate model shards, training workers or evaluation tasks across the right GPUs.
Split the model across a connected GPU group.
Orchestration layer
Model memory · connectivity · priceCoordinated model execution
Each GPU holds part of the model. The group works together to serve the request.
The same GPU can carry very different prices. We compare eligible offers and place your workload where the economics make sense.
Memory, capacity and connectivity still have to fit. Once they do, why pay more?
for the same GPU model.
$1.10 saved per GPU-hour in this example.
From a workload request to its final record, the coordination stays with the work.
Set the workload, required resources and spending limits.
Match eligible compute to the execution layout the workload requires.
Launch the work and track the GPUs and workers that run it.
Keep placement, price and run state with the result.
Start with inference. Explore models and pricing, then connect your application with an API key.
Distribute model execution across GPUs. Access leading models through one familiar API.
Explore inferenceTurn task outcomes into training signals, then evaluate the next checkpoint against your definition of success.
Explore post-trainingChoose a model, create your account, and make your first inference request.