Rent the capacity your projects need with Capordia. Start with the number of tasks and the memory per GPU, then choose the bundles and the period that make up your budget.
Choose my team's budgetOne A5000 lot for a team task: a 24 GB card and an explicit period budget. Include preparation, transfers and result retrieval within those three days.
USD 23.571 lot(s) × USD 23.57 · 3 days
1 GPUs in total · 24 GB per GPU
Two RTX 4090 lots: two GPUs in total and 24 GB per GPU. Select 2 lots in the configuration to get this weekly budget.
USD 220.002 lot(s) × USD 110.00 · 7 days
2 GPUs in total · 24 GB per GPU
A single lot already includes 2 GPUs of 180 GB each. Select 1 lot for seven days; the total is not to be multiplied by two again.
USD 2,071.001 lot(s) × USD 2,071.00 · 7 days
2 GPUs in total · 180 GB per GPU
Compare with the 80 GB H100 SXM to keep the task on a single GPU, if that capacity and the software are suitable. Adding 24 GB lots suits independent workloads; it does not merge memory.
Direct crypto payment, no required top-up. Capordia accepts crypto payment without requiring an ID document or a KYC process in this ordering flow. An account with first name, last name, email and password is required; this is not an anonymous purchase. In particular, you can choose BTC on Bitcoin or USDT on Tron TRC-20.
View all assets and networksBefore committing to the plan, have the CPU resources, host RAM, storage, network, topology, region and schedule that your project depends on specified. The displayed quantity does not reserve a future slot. Your team prepares and validates its software; the configuration is not a ready-to-use application. External fees, taxes and commercial documentation remain for you to verify for your purchase.
A team may need an inference environment for an internal tool, a business presentation or a validation phase. Define the usage hours, the expected concurrency and representative input sizes. The choice of memory must be weighed against the model and its settings, then verified with requests that resemble daily work.
Also plan for what the user will see when processing is busy or interrupted. A queue, an explicit message and a recovery procedure can matter more for operations than an isolated measurement obtained on a single request.
To classify documents, produce renders or enrich a dataset, start by identifying the unit of work and the expected output. Organize the batches so you can tell which are finished and which need to be resumed. Several cards can be used to distribute independent tasks if your application and your organization allow it.
Set a deadline for new jobs and another for the final export. This separation prevents the whole available window from being taken up by compute when results still need to be consolidated and checked.
A rental period can be used to rebuild an environment and verify how it runs before moving the main workload. Keep a data sample, a launch procedure and a comparison of outputs. The expected result is a handover file the team can use, with known deviations and decisions taken.
When several people share a compute schedule, assign time slots, directories and responsibilities. Keep each job's settings separate and plan a checkpoint between two workloads. Your team keeps control over the software and the content of the processing; explicit organization supports that autonomy and limits unnecessary rework.
Set admission, priorities and resumption rules for a shared queue.
Arbitrate between several projects, reserve margins and build a capacity schedule.
Hand over the actions, the limits and the responsibilities to another person.
Several bundles provide several GPUs, useful for independent tasks. If a single task exceeds one card's memory, compare a higher capacity per GPU, such as the 80 GB of an H100 SXM. Splitting across several cards must be supported by the software and the topology.
Choose two lots of 1 RTX 4090 GPU over seven days: 2 × USD 110.00 = USD 220.00. Each GPU keeps 24 GB. The link pre-fills the duration; choose 2 lots in the configuration.
No. The B200 plan already covers two GPUs with 180 GB each. One lot over seven days costs USD 2,071.00. Two lots would mean four GPUs and a total multiplied by two; the memory does not merge automatically.
Include preparation, transfers, tests, runs and result retrieval within the chosen 3, 7 or 30 days. No automatic renewal is planned. The supply schedule and the resources your software needs must be agreed before purchase.
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