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Launch instances and manage your compute resources.
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Launch self-serve GPU compute for demanding work.
Store and Compute still use separate accounts today. We’re working on a unified account experience.
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Training and fine-tuning with Compute
Train and fine-tune models on the stack you already know
Launch 4090 and 5090 instances, start from familiar templates, and keep training costs easier to control with per-second billing and all-inclusive pricing.
Why teams choose Compute for training
Start from familiar images
Use Ubuntu, PyTorch, and Jupyter Notebook integration to get moving quickly without rebuilding your environment from scratch.
Save repeatable setups
Turn a working environment into a custom template and reuse it for future runs.
Pay for what you use
Use per-second billing with pricing that already includes compute, storage, and data transfer.
Scale with the job
Move from smaller experiments on a single GPU to larger multi-GPU runs when the workload needs more headroom.
How it works
Swipe left to see more
Choose the 4090 or 5090 tier that fits your model size and training pattern.
Start from Ubuntu or PyTorch, and open Jupyter if that fits your workflow.
Bring your datasets and scripts into the instance using your own tools, notebooks, or containers.
Run your training job, watch progress, and save the environment as a custom template for next time.
Training patterns teams use most
Most teams do not need the same setup for every job. Compute is flexible enough for smaller experiments, heavier fine-tunes, and notebook-led exploration before moving into longer runs.
Start small when you are testing LoRA runs, checking data quality, or validating a setup.
Move to larger 5090 tiers when the job needs more VRAM and memory headroom.
Use notebooks when you want to explore quickly, then move the same work into a more repeatable training setup.
Pricing at a glance
We offer on-demand for time-critical runs. Billing is per second and all-inclusive.
RTX 5090
1 × - 8 ×
vCPU - - -
RAM - - - GB
Disk space - - - GB
Bandwidth - Mb/s
RTX 4090
1 × - 8 ×
vCPU - - -
RAM - - - GB
Disk space - - - GB
Bandwidth - Mb/s
Start self-serve, go deeper when needed
Try Compute directly if you want to test workflow fit, environment setup, and training costs for yourself.
Talk to sales if your team needs rollout planning, larger deployments, support options, or a deeper commercial conversation. We can also help model the path before a pilot when the project is more complex.
Questions teams usually ask
