Choose IteraGPU to fund a specific ML campaign: we rent out the capacity for your protocol, at one price for the whole period. Start at USD 23.57 for 1 lot of NVIDIA RTX A5000 24GB, i.e. 1 24 GB GPUs for 3 days, payable directly in crypto with no KYC or forced top-up.
From USD 23.571 lot of NVIDIA RTX A5000 24GB · 1 GPUs · 3 days
Direct payment, no prior top-up. Account required: first name, last name, email and password. No KYC procedure and no ID document.
1 GPUs included · 24 GB per card · GDDR6 ECC
Package total · 3 days
USD 23.5751 cards available.
Rent this configurationWe offer A100 SXM with 80 GB at USD 280.00 and MI300X with 192 GB at USD 450.00, each for 1 lot of 1 GPU for 7 days. Choose the capacity for your complete cycle: A100 for a compatible NVIDIA experience, MI300X for a qualified AMD ROCm/HIP chain, extensions included.
Choose the memory and backend for my adaptationThree, seven or thirty days: we display the lot price for the entire period. Choose the package that covers your trial program and its evaluation; no automatic renewal extends your commitment.
View full packagesPay for your package directly in crypto, without topping up 100 USD first. Our flow requires neither an ID document nor a KYC procedure; your account tracks the order. For a one-off campaign, choose this direct payment and keep topping up as an option.
Choose crypto payment without KYCNVIDIA RTX A5000 24GB
USD 23.571 GPUs total · 24 GB per card
Lot price: USD 23.57
Spend three days on a first trial: baseline run, memory measurement and saving results, with your prepared protocol.
1 lot to configure.
NVIDIA A40 48GB
USD 136.002 GPUs total · 48 GB per card
Lot price: USD 68.00
Assign a 48 GB card to each variant. Work on the same corpus and the same criteria, with a shared budget for both experiments.
Choose 2 lots in the configurator.
NVIDIA A100 SXM 80GB
USD 990.001 GPUs total · 80 GB per card
Lot price: USD 990.00
Keep an 80 GB card for thirty days to organize your test series, resume your experiments and gather their results.
1 lot to configure.
Each scenario corresponds to its own duration and quantity. These totals serve to choose a work schedule, not to rank GPU speed.
Rent with crypto without KYC: assets, networks and account required →
15 configurations · Totals in USD for 3 days
24 GB per card · GDDR6 ECC
Package for one card.
24 GB per card · GDDR6X
Package for one card.
48 GB per card · GDDR6 ECC
Package for one card.
24 GB per card · GDDR6
Package for one card.
48 GB per card · GDDR6 ECC
Package for one card.
24 GB per card · GDDR6X
Package for one card.
48 GB per card · GDDR6 ECC
Package for one card.
48 GB per card · GDDR6 ECC
Package for one card.
32 GB per card · GDDR7
Package for one card.
80 GB per card · HBM2e
Package for one card.
80 GB per card · HBM2e
Package for one card.
192 GB per card · HBM3
Package for one card.
80 GB per card · HBM3
Package for one card.
141 GB per card · HBM3e
Package for one card.
180 GB per card · HBM3e
Package for a batch of 2 cards.
The plan covers the number of cards shown for 3, 7 or 30 days. You then choose from 1 to 10 lots in your order. The B200 lot contains two cards; the other configurations have one card per lot.
Prices are shown in USD. You can pay for the order in crypto or use your available USD balance. The summary keeps the configuration, duration and quantity you selected.
Compare durations · Choosing your payment networkSeparate groups, duplicates, and data uses to build a held-out ML evaluation set that is controllable and suited to your decision.
Calculate the KV cache using KV heads, context and concurrent sequences. Distinguish GQA, precision and static cache before a real trial.
Build an ML ablation plan with a control, factors, interactions and a trial budget. A worked example to prioritize variants and reach a conclusion.
Analyze classification and extraction errors: confusion matrix, references, taxonomy, regressions and verification of the next fix.
Start with the exact software and model, then the work to be executed. The catalog's nominal capacity is listed per card: two GPUs don't automatically form a single memory pool. Advertised GB and measured GiB must be compared with their units made explicit.
| Your decision | Inputs to pin down | What makes the choice possible |
|---|---|---|
| Handling the load | Weights, precision, context in tokens, and concurrent requests | A peak measured with your representative inputs, plus a justified margin; weight size alone isn't enough. |
| Getting an acceptable output | Corpus, quality rule, and threshold set before the tests | The candidates that preserve the expected quality; high throughput doesn't compensate for a rejected output. |
| Committing to the right plan | Setup, measurements, resumptions, and export in 3, 7, or 30 days | The full price in USD per batch, multiplied by the number of batches; no output volume inferred from the schedule alone. |
Validate the load, then the phase that consumes the most memory. For inference, test the intended context and concurrency. For training, include the backward pass and the optimizer. A small successful case doesn't establish the capacity of the full workload.
Preparing an inference testNote the model version, the controlled parameters, the quality, and the observed measurement. Keep failures along with their cause. The ML notebook stores your notes; it does not automatically collect telemetry and does not save your compute files.
Calculating a first budgetOur sizer estimates the dense volume of the weights with the reserve you choose. Use this envelope to prepare your selection, then measure the peak of your workload's full cycle.
The experience log keeps your assumptions and your budget. You can then tie the chosen configuration to your success criterion and to the results to be evaluated.
Size my experimentIteraGPU Lab v1 brings together a notebook, the measurement scripts and a blank results table. Choose this framework to record your measurements and compare your trials at constant quality.
The Lab provides preparation tools; its limits and its instrumentation trial are detailed in the method. Your workload's performance is measured on the chosen configuration.
Prepare my comparison protocolNotebook, scripts, protocol, pricing and blank raw table. Original code and documentation under MIT license; prerequisites and limits included.
Prepare a full step, track peak memory, and validate that the state needed to resume is saved. Then compare settings without changing your dataset along the way.
Prepare the protocolFor inference, make context and request count central to the test. Measure the first response, generation, and quality with inputs representative of your project.
Prepare the protocolA fine-tuning run is judged against the base model. Define the data split, the metric, and the examples the adaptation should improve before multiplying variants.
Prepare the protocolRenting requires no ID document or KYC procedure. Your order details stay simple: first name, last name, and email.
Understanding payment without KYCYou define your software, models, and processing. IteraGPU does not inspect the content of your files, prompts, or computations. You can organize your own comparisons and keep your working methods.
The order flow shows the network, amount, and payment address. After your transfer, "I've paid" records the report; your account lets you track its verification and access preparation.
Data and privacyDistinguish weights, cache and activations, measure allocated and reserved by phase, then choose a margin with a notebook and a PyTorch protocol.
Read the guideMETHOD / 02Fix the quality, measure the same corpus and compare the full cost of 3-, 7- or 30-day GPU plans. Protocol and raw table available for download.
Read the guideMETHOD / 03Break down an ML campaign, prioritize variants, and tie the GPU package to useful results, with an example schedule and budget in USD.
Read the guideA rental ends, but a good observation stays usable. Keep the exact model, parameters, code version, and conclusion with your order reference. The ML notebook helps you find why you settled on a setting, and what to check on the next run.
Sort the successful variants, those that exceed memory, and those whose quality is unacceptable. Then decide whether you need more capacity, a different format, or a better-targeted protocol. You can return to the catalog with a measured requirement.
Open my notebookChoose the IteraGPU NVIDIA RTX A5000 24GB package at USD 23.57 for 1 lot of 1 GPUs with 24 GB for 3 days if your workload suits that capacity. The amount covers the entire rental and is paid directly in crypto, with no prior top-up. The flow is without KYC or ID document, with first name, last name, email and password for the account. Your wallet may charge separate sending fees.
IteraGPU ties your campaign budget to a per-GPU memory, a backend and a period of 3, 7 or 30 days. Our listings let you choose 24, 80 or 192 GB according to the complete cycle of your adaptation and your software stack. You pay a defined capacity package; you keep the choice of model, code and your evaluation criteria.
Yes. IteraGPU lets you order without a KYC procedure or ID document. Your account uses first name, last name, email and password and keeps track of your rentals and payments. This absence of KYC applies to the IteraGPU flow; your wallet or sending platform applies its own rules.
At IteraGPU, choose 7 days for a defined series of trials or 30 days for a tracked campaign, including evaluation, reruns and export. The price covers the lot for the entire period, with no automatic renewal. The listings show both amounts: you settle on the window for your protocol before ordering.
You know your workload and your backend: we give you the choice of memory, period and amount committed. Pick your GPU, then pay the package directly in crypto without KYC.
USD 23.57 for 1 lot of NVIDIA RTX A5000 24GB · 1 GPU with 24 GB · 3 days.