NVIDIA A100 SXM 80GB
USD 120.003 days · 1 lot · 1 GPUs · 80 GB per GPU
Configure 3 daysView full detailsIteraGPU / GPU configurations / NVIDIA A100 SXM 80GB
Location GPU / NVIDIA A100 SXM 80GB
A100 SXM 80 GB: give your ML protocol some room.
Give your ML protocol 80 GB per card. IteraGPU rents the A100 SXM so you can reproduce an Ampere baseline, compare your adaptations, and choose a period that covers your experiments and their evaluation.
From USD 120.003 days · 1 lot · 1 GPUs · 80 GB per GPU
Crypto without KYC. Account required: first name, last name, email and password. No KYC procedure and no ID document.
Your rental3 / 7 / 30 days
NVIDIA A100 SXM 80GB
1 GPUs included · 80 GB per card · HBM2e
Package total · 3 days
USD 120.0078 cards available.
Rent this configuration- GPUs per lot
- 1
- Memory per GPU
- 80 Go
- Memory type
- HBM2e
- Available lots
- 78
Choose the period for your campaign.
Price in USD for a full lot; from 1 to 10 lots in the configurator. The total is the plan multiplied by the lots, with no automatic renewal.
NVIDIA A100 SXM 80GB
USD 280.007 days · 1 lot · 1 GPUs · 80 GB per GPU
Configure 7 daysView full detailsNVIDIA A100 SXM 80GB
USD 990.0030 days · 1 lot · 1 GPUs · 80 GB per GPU
Configure 30 daysView full detailsChoosing 80 GB for the full loop, not just the weights
The A100 SXM is a candidate for reproducing a training recipe, evaluating an adaptation, and comparing variants on the same hardware. Its 80 GB per card offers a larger envelope than 48 GB configurations; the practical benefit depends on the peak of your training step and your evaluation.
Add up the requirements of the weights, activations, gradients, and optimizer for your method. For an adaptation with few trainable parameters, activations still need to be taken into account. If your workload already fits comfortably within 48 GB, also compare an RTX A6000 before committing to the plan.
You pay for the rental directly in crypto, with no forced top-up and no KYC or ID document. The order account requires first name, last name, email, and password.
- Recipe already built around Ampere: keep its versions and numerical choices to establish your baseline.
- Workload constrained by 48 GB: examine the peak of the full loop and the target microbatch before choosing 80 GB.
- Comparison with an H100 SXM: the capacity remains 80 GB per card; compare the cost and the results of your own workload.
Campaign example · 7 days
One week to reproduce a baseline and examine an adaptation
Budget USD 280.00 for an A100 SXM lot, that is one 80 GB GPU for 7 days. Prepare the starting checkpoint and the evaluation set, then split your schedule between reproducing the baseline, trying an adaptation, evaluation, and export. The plan sets the rental budget; the number of experiments you can run depends on their measured duration.
USD 280.00
7 days · 1 lot · 1 GPUs · 80 GB per GPU
Configure this 7-day packageTwo alternatives to compare depending on your workload.
NVIDIA H100 SXM 80GB
USD 475.007 days · 1 lot · 1 GPUs · 80 GB per GPU
Worth comparing if you want to examine a more recent generation while keeping 80 GB per GPU. Moving to H100 does not, by itself, solve a need for more than 80 GB of memory.
Configure 7 daysView full detailsNVIDIA RTX A6000 48GB
USD 82.007 days · 1 lot · 1 GPUs · 48 GB per GPU
Worth considering if your training and evaluation fit within 48 GB with room to spare. Compare the plan and the support for your CUDA extensions on this other Ampere configuration.
Configure 7 daysView full detailsPay for your rental directly in crypto.
Direct payment with no prior top-up, including BTC on Bitcoin or USDT on Tron. Account required: first name, last name, email and password. No KYC procedure and no ID document.
View assets, networks, and payment termsChoose your rental: the useful answers.
Why choose an A100 SXM for a fine-tuning campaign?
The IteraGPU A100 SXM provides 80 GB of HBM2e on a single card. It is a candidate when your adaptation exceeds the 48 GB envelope or when you want to keep an Ampere baseline. The method, the trainable parameters, and the length of the examples determine the requirements; the model name alone is not enough to choose.
What budget should I plan for an A100 SXM lot?
An IteraGPU lot includes one 80 GB A100 SXM. Its full plan costs USD 120.00 for 3 days, USD 280.00 for 7 days, or USD 990.00 for 30 days. For several lots, multiply the plan by the number of lots chosen; these amounts are not daily prices.
Can I reserve the 80 GB for the model weights alone?
No. Execution also uses memory for activations, buffers and, depending on the training, gradients and optimizer states. Assess the peak of your full recipe, including evaluation and saving, to decide whether an 80 GB A100 GPU is suitable.
A100 or H100 SXM: which should I choose if memory is my bottleneck?
Both IteraGPU listings offer 80 GB per GPU. An H100 SXM therefore does not provide a larger envelope than the A100 SXM. If your run exceeds this capacity, look at a configuration with more memory per card or a change to the recipe; if it fits, compare the plans and your measurements on the same task.
Your protocol / your measurements
Prepare a campaign you can compare.
Reconstruct an experiment before improving it
Gather the starting checkpoint, the data version, the training/validation split and the exact parameters. A first run should answer a simple question: do we get a result consistent with the expected recipe? Keep the Python, PyTorch and CUDA versions as well as the numerical options. Setting a seed makes tracking easier, but doesn't necessarily make two different environments identical bit for bit.
Build a complete 80 GB budget
Training uses more than the weights. The activations kept for backpropagation and the optimizer states can determine the possible microbatch. Test a real step, then evaluation and checkpointing, because their footprint can differ. Activation checkpointing trades some memory for extra computation: compare its cost over your step duration before applying it broadly.
Ampere notably offers BF16 and TF32 operations. Specify the formats used by your software rather than assuming a default configuration stays unchanged between two versions. A numerical comparison becomes easier to review when these choices are explicit.
Making the A100 a useful point of comparison
The H100 SXM lets you study a more recent generation with the same 80 GB capacity. Measure the cost of reaching your target metric, not just the cost of a single step. If your workload fits comfortably within 48 GB, an A40 or an RTX A6000 can also be part of the protocol. In all cases, check the architectures targeted by the compiled extensions of your CUDA project.
Organizing repetitions and booking
Three days are enough to rebuild a baseline and test a resume. Seven days give a window for several seeds or ablations. Thirty days suit a structured series with regular checkpoints and a final export. Prepare your experiment manifest, choose the duration and number of GPUs, then complete the order details. After the crypto transfer, flag it with "I have paid" and find the job in your dashboard.
Prepare your first trial on this configuration
KV cache: calculating memory by context, GQA and batchComparing quantizations: memory, quality, and useful costMicrobatch and accumulation: computing the effective batch
The GPU spec describes a capacity. These methods help you define the inputs, the settings and the result to verify on your own workload.
Your campaign, your duration.
NVIDIA A100 SXM 80GB · USD 120.00 for 3 days · 1 lot · 1 GPUs · 80 GB per GPU.