[Reference page]() # RTX 4090: give your AI prototype a concrete budget. Move your prototype forward without buying a card for this project. Kernodeck offers rental of the NVIDIA GeForce RTX 4090 24GB, with 24 GB per GPU: a candidate for inference, image processing or a small fine-tuning job that fits within that memory. The plan starts at 47.14 USD for 1 batch of 1 GPUs over 3 days. - 24 GB per GPU - 3, 7 or 30-day plans - For your CUDA-compatible application [Configurer the RTX 4090 · 7 days]() At Kernodeck, no ID and no KYC process on this GPU rental path. Account required: first name, last name, email and password; that does not mean anonymity. Location NVIDIA GeForce RTX 4090 24GB A 24 GB card, a period of your choosing, a budget for your tests. ## Key facts | Fact | Detail | | --- | --- | | Your configuration | NVIDIA GeForce RTX 4090 24GB : 1 batch of 1 GPU, 24 GB per GPU. | | Your plans | 3 days: 47.14 USD ; 7 days: 110.00 USD ; 30 days: 390.00 USD. USD price for the entire batch, including all its cards. | | Availability | 265 declared batches. Declared quantities per model in the offers. They do not reserve future availability or a delivery date. Hosting country and served region to be confirmed before purchase if your project requires them. | | No KYC | At Kernodeck, no ID and no KYC process on this GPU rental path. Account required: first name, last name, email and password; that does not mean anonymity. | | Setup | Ubuntu, PyTorch, Blender or a custom request. Versions, CPU, RAM, storage, network and access mode to be confirmed per project; their inclusion is not implied by the GPU model. | | Pricing and terms | USD amounts for the lot and the entire period. Tax status and any fees to be confirmed in the applicable terms. | ## Available plans Total price in USD for one lot and the full period. Memory is shown per GPU; declared stock is expressed in lots. | Model | Memory per GPU | GPUs per lot | Duration | Lots | Total price | Declared stock in lots | Status | Configuration | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | [NVIDIA GeForce RTX 4090 24GB]() | 24 Go | 1 | 3 days | 1 | 47.14 USD | 265 | The full batch for 3 jours. | [Configure this plan]() | | [NVIDIA GeForce RTX 4090 24GB]() | 24 Go | 1 | 7 days | 1 | 110.00 USD | 265 | The full batch for 7 jours. | [Configure this plan]() | | [NVIDIA GeForce RTX 4090 24GB]() | 24 Go | 1 | 30 days | 1 | 390.00 USD | 265 | The full batch for 30 jours. | [Configure this plan]() | | [NVIDIA L40S 48GB]() | 48 Go | 1 | 7 days | 1 | 148.00 USD | 74 | Compare the 7-day budget and the memory per card. | [Configure this plan]() | | [NVIDIA RTX A5000 24GB]() | 24 Go | 1 | 7 days | 1 | 55.00 USD | 51 | Compare the 7-day budget and the memory per card. | [Configure this plan]() | ## Your application fits within 24 GB: start with that scope. You have a script that classifies documents, processes images or runs quantized inference. If its weights, inputs and temporary allocations fit within 24 GB, the RTX 4090 is a candidate worth considering. Choose it for that concrete need and for your application's compatibility with Ada, rather than for the GPU's name alone. To compare several settings on the same set of inputs, budget 110.00 USD for 1 batch of 1 GPU over 7 days. The plan gives you a spending framework; the number of runs depends on your workload. If you want to validate this scenario first, the 3-day plan costs 47.14 USD for the same batch. - [Configure my RTX 4090 for 7 days]() - [Choose a GPU for my inference]() - [Prepare my application versions]() ## More memory or a lower budget: the two useful comparisons. If the real need exceeds 24 GB, compare the L40S and its 48 GB per card before scaling down your project to make it fit. Doubling memory capacity does not guarantee throughput: the choice should still be tied to your complete application. If 24 GB is enough and budget is the priority, also consider the RTX A5000. It keeps that capacity on Ampere and offers a lower plan in the Kernodeck catalog. An application qualified for Ada must however be verified with this other architecture. - [Compare the L40S's 48 GB]() - [Compare the RTX A5000's budget]() - [Compare all GPU plans]() ## Your plan, payable directly in crypto. Pay for your Kernodeck rental directly in crypto, with no mandatory top-up: BTC on Bitcoin and USDT on Tron (TRC-20), among others. The process requires neither an ID document nor a KYC procedure; an account with first name, last name, email and password is required, with no promise of anonymity. - [Compare the eight accepted assets and networks]() ## Make the scenario fit before expanding Choose a short objective: process a set of documents, adapt a few parameters or generate a series of images. Load a complete example and note the memory peak. If the scenario fails, reduce one dimension at a time — batch, length or resolution — to understand which one governs the requirement. Gradient accumulation can help build an effective batch from micro-batches. It does not remove the need to measure the training step, whose states take up more space than a simple inference pass. ## Leaving the trial notebook behind Once the prototype works, export its steps into a script that takes an explicit configuration. Fix the model, the inputs, the package versions and the output location. A notebook run in an unknown order becomes hard to compare after several days of changes. Keep a small test that checks CUDA loading and produces a known output. It will quickly tell you if an update to PyTorch or an extension has changed the project path. ## When to go beyond 24 GB Move to the RTX 5090 if 32 GB and a compatible Blackwell stack meet your needs. Choose a 48 GB card instead, such as the RTX A6000, if allocations clearly exceed 24 GB. For an application already qualified on Ampere with modest needs, the RTX 3090 is also a relevant point of comparison. ## Giving each duration a clear output In 3 days, aim for a re-runnable script and an initial measurement. In 7 days, compare parameters without changing the dataset at the same time. Over 30 days, plan several trials with checkpoints and a summary kept outside the workspace. To rent, choose the lots, the duration and the environment, then create your account or log in. You then select the asset and the crypto network. Once the transfer is made, use "I have paid" and find the status of the order in your account. ## Questions before purchase ### What budget should I plan for renting an RTX 4090? For 1 batch of 1 RTX 4090, Kernodeck offers 47.14 USD over 3 days, 110.00 USD over 7 days and 390.00 USD over 30 days. Choose the period that matches your project; these amounts describe the full plan for the batch, not an hourly price. ### Is the RTX 4090 a good starting point for my AI application? It is a candidate if your application uses an Ada-compatible stack and if its complete execution fits within 24 GB. Quantized inference, image processing or a small fine-tuning job can fall within that scope. The size of the model files alone is not enough to decide. ### When should I prefer the L40S over the RTX 4090? Compare the L40S when the RTX 4090's 24 GB limits your inputs, your dataset, or your application's state. Its 48 GB per GPU offers more capacity. This choice addresses a memory need; it is not a promise of twice-as-fast processing. ### Can I use the plan as a managed inference API? The plan covers GPU rental. You choose and prepare your application; an API ready to call, its deployment, and a given throughput are not included in this description. If you are looking for a managed API, have this need confirmed before choosing this plan. ## Choose and configure - [Moving from prototype to tracked adaptation]() - [Making your script re-runnable]() - [Compare with 32 GB on RTX 5090]() - [Consider moving to 48 GB]() - [Compare GPU plans]() - [The eight accepted crypto pairs]() - [Choose a capacity for inference]()